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The Effects Of Added Transportation Capacity





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                 Travel Model Improvement Program

The Department of Transportation, in cooperation with the
Environmental Protection Agency and the Department of Energy, has
embarked on a research program to respond to the requirements of
the Clean Air Act Amendments of 1990 and the Intermodal Surface
Transportation Efficiency Act of 1991.  This program addresses the
linkage of transportation to air quality, energy, economic growth,
land use and the overall quality of life.  The program addresses
both analytic tools and the integration of these tools into the
planning process to better support decision makers.  The program
has the following objectives:

1.   To increase the ability of existing travel forecasting
procedures to respond to emerging issues including;
environmental concerns, growth management, and lifestyle along
with traditional transportation issues, 

2.   To redesign the travel forecasting process to reflect changes
in behavior, to respond to greater information needs placed on
the forecasting process and to take advantage of changes in
data collection technology, and

3.   To integrate the forecasting techniques into the decision
making process, providing better understanding of the effects
of transportation improvements and allowing decision makers in
state governments, local governments, transit operators,
metropolitan planning organizations and environmental agencies
the capability of making improved transportation decisions.

This program was funded through the Travel Model Improvement
Program.

     Further information about the Travel Model Improvement Program
     may be obtained by writing to:

                 Planning Support Branch (HEP-22)
                  Federal Highway Administration
                 U.S. Department of Transportation
                      400 Seventh Street, SW
                      Washington, D.C. 20590





The Effects of Added
Transportation
Capacity
       
Conference Proceedings
December 16 and 17, 1991
            
Prepared by
            
Gordon A. Shunk
Texas Transportation Institute
1600 East Lamar Boulevard, Suite 120
Arlington, Texas
                  
Funded by
                  
U.S. Department of Transportation
     Federal Highway Administration
     Federal Transit Administration
     Office of the Secretary

U. S. Environmental Protection Agency
                                 
Distributed in Cooperation with
                               
Technology Sharing Program
Research and Special Programs
Administration
U.S. Department of Transportation
Washington, D.C. 20590
                
DOT-T-94-12
                                 
                                 

                                 
                                 
                             Contents
                                 
Day One: Describing the Problem . . . . . . . . . . . . . . . . . 1

Transportation Investment and Metropolitan Economic Development:
A Reconnaissance of Research Availability and Requirements
Alan E. Pisarski. . . . . . . . . . . . . . . . . . . . . . . . . 3


Effects of Added Transportation Capacity on System Performance
Richard H. Pratt. . . . . . . . . . . . . . . . . . . . . . . . . 7


The Effects of Added Transportation Capacity on Travel
Ryuichi Kitamura. . . . . . . . . . . . . . . . . . . . . . . . .11


Effects of Added Transportation Capacity on Development
Michael V. Dyett. . . . . . . . . . . . . . . . . . . . . . . . .17


Other Effects: Institutional and Financial Context
Sheldon M. Edner. . . . . . . . . . . . . . . . . . . . . . . . .23

                                 i





Day Two: How to Address the Problem . . . . . . . . . . . . . . .31

Environmental Effects of Added Transportation Capacity
John H. Suhrbier. . . . . . . . . . . . . . . . . . . . . . . . .33

Forecasting Models
Daniel Brand. . . . . . . . . . . . . . . . . . . . . . . . . . .41

Experimental Design
Peter Stopher . . . . . . . . . . . . . . . . . . . . . . . . . .47

Closing Discussion. . . . . . . . . . . . . . . . . . . . . . . .55

                                ii



Appendix -- Conference Papers
                                                                 57

The Travel Effects of Added Transportation Capacity
Gordon Shunk                                                     59

Transportation Investment and Metropolitan
Economic Development: A Reconnaissance of
Research Availability and Requirements
Alan E. Pisarski                                                 63

The Effects of Added Transportation
Capacity on Travel: A Review of Theoretical
Ryuichi Kitamura                                                 79

Effects of Added Transportation Capacity on Development
Michael V. Dyett                                                 97

Institutional, Financial, and Social Impacts of Induced
Transportation: Speculations on the Need for Research
Sheldon M. Edner                                                 101

Environmental Effects of Added Transportation Capacity
John H. Suhrbier                                                 103

Use of Travel Forecasting Models to Evaluate the Travel
and Environmental Effects of Added Transportation Capacity
Daniel Brand                                                      105

Travel and Locational Impacts
of Added Transportation Capacity: Experimental Designs
Peter Stopher                                                     113


iii






iv



Day One: Describing the Problem

     David, Chief of the  Programming Branch of the San Francisco
Office of the Environmental Protection Agency, opened the
conference.  He noted that one of the EPA's main interests in
participating in a conference that dealt with the impacts of added
transportation capacity was that frequently the regional offices
want to consider the potential growth inducing impact of proposed
highway projects.  Federal and state agencies often disagree on
whether or not increased capacity leads to less congestion and less
air pollution.  This disagreement, Calkins stated, has been going
on for over 10 years; but there was little in the way of unbiased,
extensive research to substantiate either claim.  For this reason,
the EPA is interested in pursuing a multi-agency, multi-year study
that will address this issue.
     Calkins outlined several benefits that should evolve from this
discussion.  Overall, developing information that can be used to
improve the p g and decision-making process in air quality and
transportation projects will reduce conflicts.  By being more
knowledgeable about the actual effect of added capacity,
transportation and air quality plans can be coordinated more
effectively.  Modeling procedures can also be improved as more and
better information on travel behavior is developed.  The conference
will assist in developing the state implementation plan control
strategies of the 1990 Clean Air Act Amendments (CAAA), as well as
support measures of the Intermodal Surface Transportation
Efficiency Act (ISTEA).  Other benefits include more cost-effective
air quality improvement strategies and better justifications and
alternatives to the public for transportation control measures. 
There should also be a focus on access, not just on mobility and
ease of travel issues.  Access issues include providing
transportation facilities for the elderly, the poor, the young, and
the handicapped.
     Calkins stressed the importance of study design and the need
to include all interested parties at the outset of the study,
including Metropolitan Planning Organizations (MPOs), federal
agencies, local air quality agencies, environmental groups, and
land use planners and developers.  A long-term funding commitment
from all of these organizations will be necessary for a successful
study.
     In conclusion, Calkins stated that the conference was an
opportunity to improve the quality of life, as health is the basis
for the CAAA and air quality regulations.  By learning about how
travel growth patterns interact with existing infrastructure and
other factors, transportation and land use systems can be designed
that are efficient, clean, and provide good access to services,
jobs, and recreation.
     Kevin Heanue, Director, Office of Planning of the Federal
Highway Administration, felt that the conference was a step in
seeking a broader audience in laying out a research agenda on the
issue of the impacts of added transportation capacity.  By
identifying major and minor topics to address, better guidance can
be provided to those MPOs that are involved in air quality analysis
and state implementation plan updates.
     Heanue stressed the importance of eliminating the use of
environmental specialists only at a project's end.  By bringing
environmental resources into the project at the outset and
integrating those efforts with the planning efforts, the
relationships between air quality, travel, and development will be
better understood.  As an example of an effort to promote this
integration, Heanue said, the FHWA merged the offices of
Environment and Planning in to one unit several years ago.  The
FHWA also has a policy to foster strong linkages with the
environmental community.  This is reinforced in the CAAA and ISTEA
legislation.
     The responsibilities of the are changing, Heanue said.  There
is a broader analytical framework within which there are more
choices than the traditional highway option; there are





highway transit options, for example.  The MPOs are in a position
to make the initial recommendation whether transportation
investments are highway or transit.
     Heanue said that a need exists for increased environmental
research and more accuracy and sensitivity in the present models. 
By asking the questions of whether or not latent demand or induced
traffic is a valid concept, and how new capacity affects new travel
behavior, there will be new feedback for the modeling process.  He
then stated the need for simpler modeling mechanisms, as opposed to
the modeling processes of the early 1960's.  What is needed are
logical and practical models that recognize the accuracy of the
base data and target objective.  Heanue then concluded his remarks
by suggesting that there were two agendas to approach at the
conference.  One was the research agenda, where to invest the
research money for the best results, and the other was the
practice.  What can be learned from the study that would benefit 
the 280 MPO transportation planners who would be faced with the 
implementation and technical responsibilities of the CAAA and ISTEA?
     Edward Weiner, Senior Policy Analyst with the Office of the
Secretary of Transportation, served as moderator for the first
session and offered a conclusion to the introductory remarks.  He
noted that it was encouraging to see the cooperation between the
EPA and the Transportation Department in the effort to implement
the various provisions of the CAAA.  He also reiterated the general
questions that the conference would be trying to address.  First,
what is known about the relationship between the various phenomena
involved and the effect of added capacity and induced travel?
Second, what are the key variables involved? And, third, can a good
understanding of how to measure the process be gained in order to
design impact or measurement studies that will successfully measure
this phenomena?

2




Transportation Investment and Metropolitan Economic Development:
A Reconnaissance of Research Availability and Requirements


Alan E. Pisarski

     This presentation outlined available research and literature
for a research effort on land use impacts of major rail and related
investments.  The presentation consisted of three main topics: a
review of the findings of a research and literature review, a
discussion of ways to expand on the review, and questions that will
be beneficial to the intent of the conference.
     One of the major findings of the literature review is that the
subject of land use impacts is debatable, as there is no common
terminology throughout the literature.  Material is available in
all aspects of transportation research including land use
development, economic development, impact analysis, and efficiency
studies.  The material also extends into other disciplines such as
economics, geography, and sociology.  Several consistent elements
are evident, in spite of the disparity of sources.  There is a
tendency to focus on the economic effects of investment, most
noticeably the employment and construction effects.  The economic
effects are further divided into direct, indirect, primary, and
secondary influences.  The older literature focuses more on the
traditional logistical models of the coal or steel industries and
their relation to transportation, while the newer materials looks
at the new economic effects of the service industry.  The ability
to include the transportation element in the new service-oriented
economy is not well developed.  Finally, for the most part, the
literature centers around major transportation projects, such as
San Francisco's Bay Area Rapid Transit (BART) project The emphasis
and analysis on these large undertakings has been on generational 
effects, demand changes, and land use effects.  Several problems 
are evident with the before-and-after impact studies generated from 
the large projects.  Often, these studies were under-funded and never 
completed; or after long periods of time, the findings are irrelevant,
given the changes that occurred. 
     Over the years, highway analysis shifted from attempts to
justify the facility in terms of its development effects to a more
conciliatory tone of how to solve development-generated problems,
such as congestion and environmental impacts.  There currently is a
shift back to the economic development argument as more projects
such as toll roads are being considered by private developers or
public/private cooperatives.
     The aviation sector can be studied as an example of economic
development.  The aviation industry, airports, and air travel
capability are a considerable economic engine in any region.  Few
of  the studies reviewed for the presentation focus on the changes
in the total economic capability and comparative advantage of a
region as a result of changes in local transportation.  Aviation
can be one of the dramatic economic drivers in a community.  This
is an area in which to study changes in investments and services
and the impacts they have on regional economic climates and
developments.
     One question that arises from the available research is, is it
possible to get beyond a basic assumption that transportation is a
necessary, but inconsistent, condition of growth? Additional
questions generate from this; for

3




example, why is there growth adjacent to some transit stations, but
not others? What are the positive and negative effects of density?
Why are some areas revived by transit development and others are
not?
     The question of latent demand for local travel is an important
element of added capacity impact studies and should be the center-
piece of new research topics.  How much of travel demand is latent?
How do various groups manifest this demand? The tourism industry
assumes that there is an enormous quantity of latent demand, and
they provide the means and opportunity for demand satisfaction. 
There is little research available on latent demand; however, the
National Personal Transportation Study (NPTS) data being examined
for the Federal Highway Administration are a possible source for
further study material.
     There has been an 18 percent increase in passenger miles
traveled from 1983 to 1990.  The increase is equally divided
between increases in population, average trip length, and per
capita trip increases.  Is the increase in trip rates and the
increase in trips per capita a manifestation of latent demand? If
the average trip length increased from 8 to 9 miles, are people
better or worse off; and what is gained by the extra mile, greater
choice, greater opportunity, lower housing costs, better jobs, or
wasted effort? Almost every urban trip culminated in an economic
transaction or something of social value, and the shift from latent
to actual travel demand should be suppressed.
     The increase in travel demand is partially the result of
social changes.  Also, uses of alternatives to the single occupant
automobile has declined, automobile occupancies were down and
transit use, walk to work, and telecommuting have all declined. 
Average travel times have also decreased.  The social changes that
have had an impact on travel demand are an increase in the vehicle
miles traveled by females which has risen 50 percent since 1983 and
an increase in single occupancy vehicle use for trips to work by
the poor, as examined by the American Housing Survey.  All of these
changes are part of the democratization of travel which is being
encouraged by the low cost of transportation in America.
     In conclusion, Mr. Pisarski commented on the feasibility of
travel pricing.  There is concern that there will be adverse
effects on lower income populations if pricing mechanisms are
initiated.  It will be critical to consider who will be priced out
of the transportation system by such measures and the effect this
will have on people's lives.  These considerations should become a
serious part of the research evolving from the conference.

Open Discussion
     The discussion opened with a request for Mr. Pisarski to
comment on the decrease, rather  increase, of average trip length
that was occurring in several parts of the country.  This decrease
is the result of many jobs shifting to the suburbs in contrast to a
population shift to the suburbs in search of lower housing costs. 
In some communities, these two shifts have balanced out the average
trip length.  One interesting aspect of the NPTS data was that
trips of over 30 miles to work have doubled as a percentage of all
trips.
     The question was asked if work at home, or telecommuting, had
declined.  Work at home statistics included both metropolitan
(professional employment) activities as well as traditional (rural
and agricultural) activities.  The decline in farming and rural
activities accounted for this overall decline.
     One participant noted that there were two possible research
objectives arising from the presentation: the social objective with
transportation demand elements and the economic focus at the state
and federal level.  The question of how to bring both objectives
together was posed.  The response was that while it was difficult
to coordinate both, it was important to realize how the economic
development issues manifest themselves in society.  Both economic
and social issues can be addressed, for example, in a discussion of
possible solutions to the air

4





pollution problem to get a better sense of the tradeoffs involved. 
The suppression of travel demand was all too often considered to be
a positive action, regardless of the social or economic impact
involved.  Increased awareness of the social and economic values
that are placed on travel by people is necessary.

                                                                  5





6



Effects of Added Transportation Capacity on System Performance

Richard H. Pratt

     This presentation was an overview of the effects of added
transportation capacity on system performance.  These effects are
based on several assumptions.  First, the added capacity in
question is viable if there is sufficient demand for the added
facility or service, if the facility or service is sufficiently
attractive, and if the facility or service will be used.  Second,
the added capacity is assumed to be definitely significant such as
a new arterial, freeway lane, high occupancy vehicle (HOV) lane
addition, or heavy rail transit project.
     Eight different ways in which capacity can be achieved are
identified:
  (1)  Strategic highway infrastructure (toll free, mixed traffic)
  (2)  General mixed traffic highway capacity (toll free)
  (3)  Ramp metering, other TSM, IVHS
  (4)  Toll facility capacity
  (5)  HOV capacity
  (6)  Transit capacity (on separate ways)
  (7)  Transit capacity (in mixed traffic)
  (8)  Multimodal/manageable transportation infrastructure
       (1)  Strategic highway infrastructure development could be
differentiated from generalized highway expansion in that it
attempts to provide a missing link in an existing system and,
thereby, creates good capacity.  By filling in missing links and by
removing bottleneck capacity restraints, better system use can
occur.  Transit operations would also improve because the network
on which it operates would be more complete.
     (2)  The examples given for the generalized addition of mixed
traffic capacity included a new highway that parallels an existing
highway, a conventional freeway widening project, arterial to
freeway conversions, and freeway interchange improvements.  Traffic
diverted to a new facility improves traffic flow until the system
is again overloaded.  Improvements to conventional facilities
improve, and ultimately, traffic flow is increased.  Parallel
facilities can provide traffic relief until they, too, become
congested.  Traffic flow on facilities that provide access to
improved major facilities may also increase and become congested as
drivers choose to use the major facilities.  An HOV lane that
exists on a facility where mixed traffic capability is added might
experience reduced use because the improved mixed traffic flow
reduces the incentive to use the HOV lane.  Transit operations on
the new facility, however, would be improved, provided these
operations were expressed options.  Roadway improvements that
effect increased traffic by single occupant vehicles have
detrimental effects on transit use.  Those reductions initiate a
downward spiral as transit service is reduced to maintain
acceptable operating ratios.
     (3)  Capacity that is added by actions such as ramp metering
or Intelligent Vehicle Highway Systems (IVHS) will also have
significant impacts.  Ramp metering results in the same effects as
generalized highway capacity additions; although it could be
managed, for example, by allowing HOV vehicles to bypass the
congestion.  By backing up traffic, ramp metering often increases
the amount of traffic on intersecting streets and neighborhoods and
is also problematic at interchanges.  In regard to the potential of
IVHS, there is concern that if a system were implemented that could
carry three times the present capacity of the conventional highway,
what effect would this increase have on the end points of the
system? This should be explored further in the IVHS program.
(4)  There are several general highway


                                                                  7





capacity additions that have toll capabilities.  A new toll highway
paralleling an existing highway, toll road widening, toll bridges
or tunnels, and new toll interchanges are examples.  There are
several effects to consider as a result of these potential
additions, assuming that there is no longer a financial burden and
bond holders.  Highway traffic flow on the toll facility win be
improved and controlled with the toll mechanism, and flow on
connecting and intersecting facilities might also be improved. 
Highway traffic flow on parallel facilities will also improve. 
Depending on the toll, the opportunity will arise to enhance the
HOV facilities, perhaps, by providing free HOV access.  The toll
road can also potentially become an HOV facility, by letting the
HOV riders share in the cost.  Free HOV access will also enhance
any connecting facilities.  Transit operations, too, can be
enhanced by toll usage, much like freeways.  Transit use at
parallel and intersecting facilities will be impacted depending on
the toll amount and system design.
     (5)  Possible examples of added HOV capacity include new HOV
facilities, added HOV lanes, HOV contraflow lanes where traffic is
imbalanced enough to truly add capacity, and HOV ramps and
interchanges.  Traffic flow is presumed to improve on the facility,
except in cases of friction between HOV and low occupancy vehicles
(LOV) on diamond lane situations with crossing traffic flows.  The
opportunity exists in this situation to manage the traffic flow
with changes in HOV occupancy requirements, however.  Highway
traffic flow on connecting or intersecting facilities will either
increase or be mitigated.  The opportunity also exists to manage
access volume with HOV ramps and interchanges, including mixed
traffic access at one location and HOV-only access at another. 
Traffic flow on parallel facilities will be enhanced by additional
HOV capacity, and HOV operation will be enhanced and made more
manageable.  HOV operations on connecting facilities will also be
enhanced.  Express transit service will be enhanced, although the
impact on service often depends on facility design elements.  HOV
facility design can have an impact on system performance.  One HOV
facility in Los Angeles allows the bus to pull directly into the
station, then exit with ease, whereas a facility in Houston is
designed where the bus has to completely exit the HOV facility,
spend approximately five minutes at the station, then reenter the
HOV facility.  Similarly, a situation exists on interstate 394, in
Minneapolis, where the buses, when utilizing the diamond lanes,
have to weave across traffic for the station exit with the rest of
the traffic, then repeat the competitive process to reenter the
facility.
     (6)  Examples of added transit capacity on separate guide ways
include new rail rapid transit and new bus rapid transit, either on
busways or on HOV lanes and facilities.  Highway traffic flow on
parallel facilities has been improved near central business
districts (CBDs) and where surface transit volumes are large. 
Traffic flow is also increased around and approaching transit
stations and terminals.  An HOV operation parallel to a separate
transit way facility often induces a minor reduction in usage. 
Transit service and capacity is enhanced, unless there are parallel
transit operations available.  If transit operations intersect,
usage will be enhanced and a major opportunity exists for
restructuring to improve circumferential and local service.
     (7)  Mobility is a key element, as the previous capacity
categories and impacts were oriented to those with access to an
automobile.  By providing transit capacity, mobility is enhanced
for that segment of the population without automobile access.
     (8)  Multimodal transportation infrastructure calls for the
provision of multiple modal options and the full integration of
those options.  Manageable infrastructure will go beyond strategic
infrastructure in that it will be designed for maximum efficiency
in operation and use through complimenting and enhancing travel
demand management.  Examples of this  of capacity include HOV and
transit capacity on separate or concurrent ways within

8





a corridor and added freeway capacity with HOV and buses.  Another
example is added transportation capacity introduced in conjunction
with transportation system management and travel demand management
     There are many expectations of multimodal/manageable
transportation capacity.  Traffic flow on the facility can be
improved and managed as demand increases.  There will also be
increased traffic flow on connecting or intersecting facilities,
but this could be addressed in the facility design.  Traffic relief
will be seen on parallel facilities, and HOV and transit operations
will be improved as a result of the HOV and transit components of
the multimodal approach.  Mobility will be improved for all sectors.


Open Discussion
     One participant suggested that the use of toll facilities
implied an obligation to engage in planning and regulatory
mechanisms in order for the facility to function properly.  The
toll mechanism could be one method to control the unused demand and
optimize the facility.  The question was raised whether public
policy issues were being considered with an increased role for
tolls and other transportation pricing mechanisms.  Mr. Pratt
replied that while toll facilities can provide advantages, his
intent was to encourage discussion of tolls and their manipulation
as an element of transportation management objectives.
     There was a brief discussion on what was described as the
poly-nucleation of American metropolitan areas.  Historically, long
distance trips have increased as a result of urban expansion, while
the opportunities for short distance trips has decreased.  The lack
of choice for people to conduct short distance trips by walking or
cycling or by making a short bus trip, and a subsequent loss of
economic opportunities available to people to meet daily needs
through shorter trips, leads to increased automobile dependency. 
The complexity of the transportation system and the lack of modal
diversity leaves people with no freedom to choose how to travel. 
However, considering the poly-nucleation of cities, a phenomena
being experienced in Europe and Japan, as well in the United
States, a large city will be comprised of a constellation of small
cities.  Within this framework the balance can be shifted back to
shorter trips within multiple centers, rather than longer trip
lengths focusing on a mono-center.  The question was asked how the
polynucleation concept would mesh with multimodal/manageable
transportation capacity in regards to different travel modes
accommodating different travel lengths.  Mr. Pratt replied by
describing a model of a modem multimodal activity center which
incorporates HOV system connections and land use designs for
pedestrian and bicycle access.  This model is very idealized and
little has been done to actually implement the concepts; and it was
suggested that it be considered as another area for research.
     The next question posed was how to determine the extent of the
effects of added capacity.  Should the extent be measured
geographically for an entire urban area or be limited, for example,
to a 5-mile corridor; and should the effect be measured over time,
as well? One suggestion was made that if added capacity were
provided in smaller increments rather in large projects, some of
the negative effects could be alleviated.  The comment was made
that one issue that had never been resolved was whether all vehicle
miles traveled (VMT) were equal or whether all personal miles
traveled (PMT) were equal, regardless of trip length.  As an
example, one participant asked if a 30-mile trip, in terms of its
demands on public investment, was more potent  a 1-mile trip.  It
was also suggested that frequently the geographical extent to which
transportation effects were studied needed to be increased.  A sup-
porting example was offered of an alternative penetrator highway
proposal in the Washington, D.C., area.  The forecast was to build
the highway only far enough into the D.C. area to serve some of the
suburban areas but not all the


                                                                  9





way into the area.  By extending the affected area analysis,
however, it was shown that the facility would be attractive for
people who, in fact, did want to drive all the way in, adversely
effecting neighborhoods and arterials.  The discussion dosed with a
suggestion that the spatial question in determining the affected
area to analyze, as well as the  element involved in the effects of
added transportation capacity, would be ideal research topics.

10





The Effects of Added Transportation Capacity on Travel

Ryuichi Kitamura

     This presentation attempts to address the question of induced
travel and other effects of added transportation capacity.  It
considers theoretical approaches as well as empirical evidence. 
The presentation is divided into three parts starting with a brief
description of the economic definition of travel supply and demand,
followed by a discussion of the paradigm of constant travel
budgets, and concluding with the problem of multiple linearity re-
gression.
     According to economists, travel demand relates to travel
costs.  For example, if the cost of time spent traveling to a
desired location is too great, fewer people will travel.  As travel
costs decline, more people will be on the road.  On the supply
side, travel costs will rise as more people use a facility.  Added
capacity will result in more use and rising travel costs.
     Travel behavior can be considered as resource allocation
behavior.  Travelers allocate a certain amount of time for travel,
and an assumption can be made that when the travel time doubles,
for example, the number of trips also doubles.  When the cost of
travel is reduced by added capacity, more people make more trips. 
This is the message from the theoretical and economic analysis of
added capacity, although it has never been verified.
     A theoretical approach to travel demand research presents the
concept of the constant travel time budget.  A fixed amount of time
exists that travelers would like to spend traveling.  One counter-
argument states that when capacity is improved and when travel
costs decline, people will use the time saved to make even more
trips.  This paradigm generates counter-intuitive results, however. 
For example, reducing transit fare creates more automobile travel,
because the money saved on transit tickets is used for additional
automobile travel.  This is one of the paradoxes that is derived
from the constant travel budget paradigm, and it is one of the
issues that should be researched.  The constant travel budget,
however, is one of the few behavioral paradigms to be developed
into an operational model system.
     One of the problems with studying the effects of added
capacity is the ecological correlation.  In the environment in
which transportation planners work, everything is correlated with
everything else.  Within the urban structure there is an activity
center or centers; and population densities and land prices tend to
decline further away from the center.  Houses may be larger and
transit service may start to decline at some point away from this
center.  All these variables are related (income is related to
residential choices, and urban density is related to car ownership
and household size) and create a highly complex environment in
which to plan because all the variables in the system are highly
multi-collinear.
     It is possible to initiate the modeling process with only one
or two variables, but by adding variables so that the model will be
more useful and policy sensitive, it may start to fall apart.  It
can be argued, then, that the solution is either to keep the model
simple or to remove all the multi-collinear variables and select a
set of relatively independent variables.  Either solution has
problems and is not very well supported, theoretically.
     By definition, induced traffic is related to trip generation,
diverted traffic is related to network assignment, transferred
traffic is related to mode choice, and shifted traffic is related
to trip distribution.  Focusing on induced traffic raises several
questions.  What is the impact of vehicle miles traveled (VMT) on
in-


                                                                 11





duced traffic? What is the impact of new or added facilities or
capacity on induced traffic?
     Based on data from 23 cities there is strong evidence that
more facilities contribute to longer trip distance, but there is a
relationship between trip length and population.  The average
speed, or network speed, should be lower with more capacity.  There
is, however, a clear indication that as the average speed rises,
trip distances also rise.  One problem is that freeway expansion
often takes place in areas of urban expansion where the population
is increasing.  It is difficult to separate the pure facility
effect from the growth effect.
     One previous study of induced travel added accessibility
majors to the trip generation equation, both attractions and
productions.  The accessibility majors were found to be
significantly in school trip production and school trip attraction
models.  This should not be the case because school trips are
similar to work trips and, therefore, should be insensitive to
accessibility factors.  The same accessibility major was used in a
corridor analysis context to establish cause and effect linkages in
this multi-collinear environment.  The link between accessibility
and trip generation had to be removed, however, in order to devise
a structure where accessibility influences automobile ownership,
which in turn influences trip generation.  The results of these
studies suggest that there are no linkages between trip generation
and added capacity and that there is no induced traffic due to the
addition of capacity.
     What is important, however, is the growth development and
growth effect that a new facility might have.  There are several
things to consider and study in this assumption.  First, it is
necessary to have a better understanding of trip timing.  One
effect of congestion on trip g is, for example, that meetings are
scheduled to begin at 10:00 a.m. and end before 3-30 p.m in order
for participants to avoid peak travel times.  For work trips,
people either leave earlier or stay later.  If more travel options
were available, the response to the work trip would be different. 
A better understanding of trip chaining is needed, as well.  Trip
timing and trip chaining are closely related; for example, a person
might choose to run an errand during lunch rather than on the way
home because of congestion.
     Even considering the difficulties in responding to a multi-
collinear environment, the complex models now being used can be im-
proved.  Erroneous estimates may be produced because the tendency
is to produce attractive models with statistics and the right kinds
of signals.  In an effort to produce these attractive models,
variables which may be counterproductive in the long run are often
removed.  It may be necessary to consider a more complex system of
equations in a consistent and statistically desirable manner.
     A wealth of data is available from origin destination studies
conducted in most metropolitan areas.  The quality may not be
consistent, but it should be possible to select ten metropolitan
areas of different sizes with good data.  By applying resources to
the data sets, cleaning them up, and supplementing those with
missing trip information, for example, the data sets should be
comparable to each other in a uniform manner.  This process could
then be expanded to include land use data and network data.  This
would be a expensive project, but the results would be a tremendous
information source for research.  This resource base would make it
possible to compare trip timing in cities of different sizes,
different densities, and different congestion levels.
     There is a limit to the theoretical approaches to studying the
effects of added capacity and a lack of consistent observations to
support any measurements of the impacts.  One solution, the use of
the longitudinal panel, provides information on changes in income,
behavior, and facility use.  This approach would be a beneficial
supplement to the traditional four-step model which is not based on
change.  Combining these two approaches might offer a better set of
observations to analyze the effects of added capacity.

12





Open Discussion
     The first question was in reference to the four-step model and
the suggestion that improvements to it are needed.  Is the
planners' understanding of the induced traffic phenomena and added
capacity sufficient at this time to warrant adjusts to the four-
step model? Or, are additional measurements needed to see if the
four-step model is even applicable at this time? Growth and the
effects of development are the first order effects, not the induced
trip effect; and the four-step process deals only with the induced
effects.  To include the additional effects will require a five- or
six-step model system.
     One participant asked how much information was available
regarding off-peak trips.  In some areas the off-peak travel
figures have increased more than anticipated.  One participant
replied that little information is available on these trips.  It
was suggested that the increase, in part, may be the result of the
increase in the female labor force.
     The question was then asked if additional variables, from a
behavioral perspective, should be collected.  Examples would be the
impact that the fear of crime has on transit ridership or the
effects of earthquakes on travel behavior.  Also, is experiential
data beneficial in studying the effects of added capacity? Related
to these issues is the time frame and geographical context of the
impacts of new facilities.  Combined, these elements create the
dynamic situation that may be impossible to cover in a traditional,
large-scale survey.
     Participants discussed the definition of "induced" and its
various interpretations.  One participant commented that separating
a highway's long-term land use impacts from the short term is
difficult.  Another interpretation of induced traffic is that which
is encouraged by added capacity.  If a new freeway is built and
travel times are improved, people will travel more often.  The
additional trips are the induced travel.
     A request was made to consider the growth stratification that
a community might experience.  Development traffic will be
encouraged by land use changes, but these changes should be
separated into those that will occur regardless and changes that
are due to the added capacity.  Natural growth, it was pointed out,
does not consider changes in land use.
     The discussion then returned to the applicability of the four-
step model to the issues of added capacity.  One participant
suggested that incremental improvements to the four-step model are
needed in the short-term, because it is often suggested that this
model is an engineering approach to a social phenomena.  Another
participant stated that these incremental improvements might be
beneficial in the short term, but were they necessary for long-term
consideration? It is important, was the reply, that long-term
considerations not divert attention from short-term necessity. 
Long-term modeling objectives can be served with advanced computing
and mathematical capabilities that were unavailable before. 
Several participants supported this view, and the statement was
made that both short- and long-term considerations need to be
addressed by adjusting existing processes and exploring completely
new frameworks for conducting travel demand analysis that go beyond
the four-step process.  These new frameworks can incorporate ele-
ments of chaos theory and mathematics and observe how land use,
transportation and travel behavior interact.
     It was then suggested that research areas should not be
constrained to data sets collected from the narrow American
transportation experiences.  The dependency of Americans on the
automobile constrains the mode choice wi a community.  Thus, the
overall transportation experience needs to be considered.  Short-
term questions, such as those related to clean air, need to be
addressed; but for long-term economic competitiveness issues such
as the dynamics of the automobile-dependent society, the
metropolitan structure, and the evolution of constraints on travel
behavior all need to be included.  Countries with high levels of


                                                                 13





affluence such as Canada, Germany, The Netherlands, and Denmark
need to be examined.  By extending the data set to incorporate
communities outside the United States with significantly different
mode shares, the impacts of pedestrian and bicycle modes and
transit-oriented cluster developments can be better understood.  It
was suggested that geographic information systems (GIS) will
support this kind of research because micro-scale land use and
urban form will be easier to incorporate into traditional research
methods.
     It was then suggested that there are straight forward ways of
modeling travel and land use (e.g., the incremental travel
forecasting procedure for transit alternatives analysis that is
being used in several cities was mentioned).  The procedure uses
long run demand elasticities based on cross-sectional data.  Travel
is divided into three components.  One is growth in travel due to
the changes which would have happened in the region without the
major transit or highway improvement.  The second is the changes in
travel which result from highway improvement and include both land
use redistributions and changes in travel and travel cost due to
the lowered price of travel.  The third is diverted travel, which
is how the travel on the particular mode in question distributes
itself among the paths in that mode.  In this instance, induced
travel is really caused by the redistribution of land uses and also
by the redistribution in travel as well, including longer trip
lengths and increased trip rates.  This can be reduced and
simplified to be almost incremental elasticity-based by applying
single variables.
     One participant responded that it is necessary to separate the
ability to model from the necessity of gaining a better
understanding of what is going on in society.  This effort may be a
large, data sensitive effort that will not necessarily be
elucidated in these models.  A concern was also expressed about the
practice of ignoring certain types of data, simply because the
methods to forecast them are unavailable and, thus, not deemed cost
effective.  A concerted effort needs to be made to understand the
current situation and then determine if the models are appropriate. 
Two elements need to be distinguished: the societal effects on
travel and the changes being made to the transportation system. 
Understanding travel behavior will benefit the comprehension of the
impacts of both these elements on travel.
     There are several contextual issues that relate to these types
of questions, one participant stated.  there is no clear idea as to
how much can be known in regard to the overall transportation and
urban systems which are so complex with everyone making travel
decisions simultaneously.  There are interactions which will never
be taken into account, and it may never be known how well the
models really represent this complexity.  No consistent set of
numbers are available to tell how large the model errors are; and,
even if there were, it would be difficult to determine if the
errors were problems in the model, the data, or modelers.  Even if
these things were known, it might not make any difference.  There
will always be a need for improvement in models, yet it is not
clear when these should be made or why.
     There is no question that more research needs to be conducted
to improve the understanding of the issues presented here, one par-
ticipant stated.  However, one of the fundamental problems remains
that many models currently in use are well behind the typical state
of the practice.  This may be due to a combination of the lack of
finances, lack of staff resources, or carelessness.  It was
suggested that by merely bringing what has been learned into the
existing models, great advances would be made.
     The relation between work and non-work trip choices and
location was then raised by another participant.  In California,
for example, so much emphasis is placed on work trips and location
choice, that a phenomenon has been ignored, that of people making
location decisions that will force them to be auto-dependent for
all other non-work trips.  The work trip can be addressed through
HOV lanes and transit facilities that provide better service for
these trips.  By choosing to live in areas of single-

14





family housing and low density, an overall travel pattern is
created.  Transportation investment decisions make a difference in
these residential location decisions.
     A question was then raised regarding politics, travel choices,
and travel behavior.  One participant observed, based on
experiences in California, that environmental groups are expressing
concerns about transportation investments that cite development as
the real issue, not whether a trip is new or redistributed.  Trans-
portation plays a role in encouraging development.  Focusing
research efforts only on redistributed trips will miss the point if
the real public concern is developmental impacts.
     General criticisms of the current state of travel models were
offered by several participants.  One general plan was described,
for example, that projects three times as much employment as
housing.  These figures were generated using arbitrary land use
inputs without using additional transportation input, thus making
the results meaningless.  Many large scale models are used
incorrectly too, by not feeding congestive travel times into trip
distributions.  This may result in similar VMT numbers across all
development alternatives, even no-build scenarios.  It was
suggested that the Environmental Protection Agency and the Federal
Highway Administration set standards for modeling agencies.  These
standards should be distinguished between short term and medium
term by encouraging the MPOs to implement land use models and the
long-term applications and improvements of the four-step model.
     The question was raised as to how freight movement relates to
the issues being considered.  Freight accounts for a large part of
traffic in metropolitan areas where interstate commerce moves into
and out of ports.  The trend toward just-in-time delivery is
increasing the amount of product inventory on the highway system
and the amount of truck deliveries.  How do capacity needs for port
access and airport connections relate to work travel? Environmental
and economic questions are relevant to both issues.
     Several concluding remarks were made, particularly regarding
the non-work trip.  One of the reasons that induced travel has not
been measured is a general failure in understanding non-work
travel.  Increasing this understanding is a primary concern which
may be addressed by developing methods to measure it more
effectively.  As non-work travel is measured currently, it accounts
for up to, 50 percent of peak period travel.  Restricting research
efforts to the work trip will not be enough when focusing on peak
period congestion.  Non-work travel must be included for
consideration of air quality issues and congestion when studying
the effects of added transportation capacity.

                                                                 15








Effects of Added Transportation Capacity on Development

Michael V Dyett

     By looking back to the transportation modeling activities of
the 19, a clear connection can be seen between land use and
transportation.  Planners are now in an age of standards, following
an age of surveys and of models.  California law now specifically
requires planners to ensure that the circulation element is
correlated with the land use element.  This means more  fitting two
maps together on the light table: it involves generating many
iterations of model runs to get the right fit and even then the
improvements must appear affordable.  The trend now is to use
different levels of service standards for different land use types,
thus requiring that the circulation element fit these varied
standards.
     Cities and other promoters of transportation facilities are in
the land development business, although they often do not fully
understand how transportation capacity affects development trends. 
Highway and transit projects are not just intended to alleviate
congestion, which may even be impossible over the long term but are
intended to enable urban development to occur.
     Added transportation capacity, both improving the existing
system and creating new facilities and services, may affect several
aspects of urban development.  The development location may be
affected by added capacity; the effect could be either a
distributional effect of or a net addition to the region or
corridor.  In studies of the Bay Area Rapid Transit (BART) system,
the distributional effects are evident, but there was no net gain
in terms of the competitive advantage of the area.  BART affected
the decisions on where to build, but it did not create markets or
add to the overall housing supply.
     The type of development can also be affected, particularly
residential versus commercial and industrial.  New highways can
increase the viability of shopping centers and mixed use facilities
as these centers are capable of drawing critical masses of people,
up to 100, 000.  Highways can also expand the commute shed and spur
housing development.  The BART impact studies also revealed a
hedging phenomenon.  Potential home buyers sought locations that
would be served by BART at a later date.  In this way, added
transportation capacity was used as a form of insurance for the
long term, and developers marketed future BART availability as an
amenity.  Development density and intensity could also be affected. 
As a site becomes more accessible, there is increased pressure for
higher density development.  The Galleria area in Houston, Texas,
is an example of high density development and transportation
capacity.  This mixed use area encompasses enough land area to be
ranked as the third largest downtown in the state.  Proposals for
new highway capacity could result in 12 freeway lanes.
     Added transportation capacity can also affect development
project timing, lease up, and occupancy.  Speculation often occurs
before transportation projects are approved and under construction;
this expectation can influence development construction timing or
leasing.
     Land use effects are traditionally determined on the basis of
changes in accessibility, as well as mobility.  These changes in
accessibility will affect peak-hour trips.  A missing link in the
effect of added capacity has been its impact on latent travel
demand, primarily related to discretionary, non-work trips.  This
latent demand may induce pressure for new development or


                                                                 17





redevelopment.  In urbanized areas the additional capacity alone
may facilitate or promote development, while in new growth areas a
whole package of facilities, including schools, water, and sewage
and drainage improvements are needed.
     The setting in which added transportation capacity occurs also
affects development.  Economic growth potential may vary from re-
gion to region, for example, Buffalo compared to San Diego.  When
the economic growth potential of an area is low, the growth-
including impacts of a transportation facility are also low.  When
there is a strong regional market with a high economic growth
potential, the growth inducements and impacts are greater through
multiplier effects.
     Land use policies such as zoning and growth management
requirements limit the effects of added capacity, but they also
enable local governments to capitalize on the benefits.  In
Freemont, California, the goal of the city was to control the type
of development adjacent to the BART line.  A density floor was set,
and the city waited until the market could meet these requirements
rather proceeding with lower density developments.
     The dimensions of new capacity are another important element
when considering impacts.  Is the added capacity an incremental
improvement to an existing facility, or is it a new highway
development?
     Location within a region is an additional dimension to
consider.  If infrastructure facility packages are in place on the
urban fringe, added transportation capacity can induce fairly high
impacts.  In an older central business district (CBD), however,
there might be low growth inducing impacts of added capacity.

     There are several strategies for dealing with development
impacts.  The primary key is effective, long-range, comprehensive,
coordinated land use and transportation planning supported by local
political leaders.  Transportation improvements and private
development projects that are consistent within these plans should
not be automatically assumed to induce growth, nor should they be
subject to separate impact analysis for air quality.  Also, these
pro" should not be subject to mitigation requirements beyond what
would be a fair share contribution to citywide improvements and
specific off-site improvements not contemplated by the local
jurisdiction's comprehensive plan.
     The decision-making process of whether to add transportation
capacity should focus on how to resolve conflicts through multi-
jurisdictional planning.  Projects that are consistent with
comprehensive plans and zoning restrictions should also be
distinguished from those requiring amendments or rezoning.  The
decision making process should include the following four steps:
1.   Design equitable proposals;
2.   Facilitate constructive negotiations within the community and
     between affected jurisdictions;
3.   Make decisions based on plans and packages of improvements,
     not individual improvement projects that are not consistent
     with land use plans; and
4.   Compensate those adversely affected.  Two types of questions
     can be posed for a research agenda: (1) general issues of
     concern regarding development impacts and (2) more specific
     questions related to the development process and the role of
     added transportation capacity in development decisions.
     A general consideration includes determining what criteria to
use where evaluating development impacts.  Safety, mobility, land
use compatibility, and the desire to influence modal split are all
elements that could be used.  Where there are level of service
standards correlated with land use, how should through traffic be
evaluated in judging local compliance? Under what conditions can
new capacity be added without growth-inducing effects? When will
new capacity contribute to "economies of agglomeration" or, in
contrast, foster more dispersed development? Does it make sense to
distinguish improvements designed to cure existing deficiencies
from improvements

18





oriented towards new development?
     A more specific question related to the development process
includes how to determine the developers' perceptions of congestion
costs.  Do developers consider congestion a cost of doing business
that is unlikely to affect project lease-up rates? Or, is the
potential for future congestion considered in overall project
value? What is the duration of the development effects that is
attributable to added transportation capacity? In relation to
system performance, are these limited in both geographic area and
in time? Does the perceived improvement in mobility from added
capacity result in a larger commute shed or greater potential
retail market with a long-term economic benefit, or are the results
short term in nature?
     Mr. Dyett concluded his presentation with a discussion of a
recent San Francisco Bay area modeling study which dealt with the
effects of the regional transportation plan on land development
patterns in 2010.  Over this period, the regional transportation
improvement plan would fund approximately $15 billion in highway
capital costs and $10 billion in transit capital costs.  The
Association of Bay Area Governments, by using their model and
studies for the Metropolitan Transportation Commission, found
little difference between the build and no-build scenarios within
existing land use constraints.  The Bay area is typified as a
coastal area consisting of highly regulated communities where the
free market does not function in an unconstrained manner.  When
land use constraints were lifted in the model, new roads had an
impact on the distribution of growth.  In some counties of the
study area, a more dispersed development pattern developed; while
in others there was a tendency toward intense development and
greater accessibility.  The study showed that new roadway capacity
could have a greater effect on land use distribution if all land
use constraints were removed, which is unlikely to happen.  The
magnitude and the nature of the effect of added capacity was also
shown to be dependent on where the new roadways were located.

Open Discussion
     The discussion was initiated by a review of a general plan
assessment conducted for Montgomery County, Maryland, in 1987.  At
that time it was found that the balance between transportation
capacity and zoned land use capacity was significantly off.  This
imbalance was the result of the common practice in the United
States of allowing a lot of latitude on commercial zoning& in
effect, to give the market the freedom to go where it wanted.  The
plan assessment determined that the system could not function
because of the dramatic imbalance between the number of jobs and
houses that was determined by the existing zoning restrictions. 
Since the assessment, changes in the zoning structure have
constrained the amount of employment which can be supported.  Addi-
tionally, a comprehensive growth policy study which considered
various scenarios for growth was conducted.  This study showed that
it would either be possible to (1) support as many as twice the
current number of jobs and houses or (2) support very little growth
within the master plan transportation infrastructure.  Either
scenario depended on the kinds of pricing policies, pedestrian and
bicycle accommodations, and travel demand management (TDM) measures
that were initiated.  The way in which the comprehensive link
between land use and transportation planning is implemented is
critical to whether or not added transportation capacity induces
growth.
     One participant commented on the use of models and the results
of the BART modeling reports.  Reservations were expressed regard-
ing the conclusions that only slight differences were found between
the build and no-build scenarios.  This result was determined by
the property of the models that were used and that they showed
little response to the transportation system because the models
used for part of the land use forecasting were models that were
heavily constrained by external inputs.  The external inputs, such
as housing stock combined


                                                                 19





with the land use constraints, essentially drove the models and
determined the output The implication was that very careful studies
of model structure and sensitivity need to be considered when
applying them to issues of added transportation capacity.
     The question was raised regarding freight movement and
transportation capacity and development issues.  Mr. Dyett
responded that freight movement was linked to industrial de-
velopment plans and ports and airports.  These transportation
facilities offer an economic advantage for firms involved in the
movement of goods, whether they locate near resources or markets or
are footloose.  If transportation costs can be minimized, an
economic advantage can be gained; therefore, firms tend to seek out
and bid up land prices that offer this advantage to the extent that
local and regional plans provide opportunity.  For example, some
ports in the San Francisco Bay area have been successful in
attempts to spur land development, increase goods capacity and
throughput, and attract economic development.
     Another participant noted that the level of service (LOS)
standard requirements that had been in place in California for
several years, and have been copied to a certain degree in the
Intermodal Surface Transportation Efficiency Act (L%TA), have
probably had more negative effects than positive.  The LOS
standards have led to down-zoning and development restrictions
because they are not based on economic analysis that determine the
best, most effective transportation service, but are based on a De-
partment of Public Works process that utilizes little land use or
planning input.  In Montgomery County, Maryland, an adequate public
facilities ordinance has been in use for years that uses both
areawide and local area standards for approving new subdivisions. 
The county permits more congestion in areas where people have
alternatives to the automobile.  Individual subdivisions are tested
to see if they cause local intersections to fail according to local
area standards.  Frequently, intersection widenings would be
required which degraded the pedestrian environment that the county
was seeking to improve.  In this way policies and LOS standards
often work at cross purposes.
     Several questions were posed for general discussion: what
knowledge about land use is needed to measure the impacts of new
highways? What kind of data needs to be collected, and how are the
measurements going to be conducted? It was suggested that the panel
discuss whether or not they were ready to measure the effect of
added capacity; and, if they felt they were not ready, what was
needed to get ready.
     One participant suggested that they were ready for
measurement, although the quality of  analysis was not consistent
throughout the country.  There is an obligation to measure the im-
pacts as there are capital commitments being made with major
environmental implications.  The comment was made that one problem
in measuring impacts is that, first, the affected area or region
needs to be defined and matched with an institution.  MPOS, for
example, do not always encompass the entire region that will be
affected by added transportation capacity.  This will create
difficulties in data collection and measurement.
     The issue was raised whether it would be possible to identify
the circumstances under which a project or program would not be
likely to trigger any sort of development or locational effects. 
Transportation agencies or air quality agencies can then proceed
with confidence that they will not be subject to litigation based
on unforeseen impacts.  Mr. Alan Pisarski replied that others
analyze transportation demand.  For example, a retail chain might
analyze how far away people are to one store and then calculate
where the next store should be located.  These sources provide
feedback that should be considered when potential impacts are
analyzed.
     The discussion continued with a comparison of the American,
Japanese, and European shopping travel tendencies.  Americans, it
is claimed, travel greater average distances to shop  do Europeans
and Japanese.  This is a function of the retail structure of the
country, 

28





and the United States has been putting pressure on the Japanese to
break up the "mom and pop" retail structure and allow for larger
regional shopping centers.  The Japanese will then become more
dependent on longer shopping trips and larger retail aggregations. 
The Europeans, too, seem to be moving towards a reliance on hyper-
markets rather  a dispersed retail environment.  This creates a
different interaction between freight and passenger systems.  The
European experience is demonstrating that by conglomerating the
retail activity, the number of trucks needed to service the hyper-
markets is reduced; but it also increases the number of passenger
trips to retail centers.  The policy tradeoff is whether more
trucks in the city are desirable because of a traditional
disaggregate retail structure, or are more passenger vehicle trips
desirable to a regional shopping center? One participant suggested
that because of these issues, the traditional transportation models
need to be adapted to represent the more dynamic system of
interactions between transportation and business.
     The United States manufacturing and service industries are
becoming more like the Japanese with an emphasis on the time of
delivery and the predictability of service delivery.  This has
different implications for the industry transportation interaction. 
An understanding of the change between the private sector and
public investment is necessary to design models for the future. 
The two most important transportation elements to the private
sector are bottlenecks and flexibility.
     The question was then asked if telecommunications will be
considered to be added transportation capacity.  Mr. Pisarski
replied, yes; the advent of increased telecommunications had
influenced the location of business and how traditional business
depends on transportation, for example, with just-in-time delivery
systems.  One of the problems with telecommuting, however, is that
by eliminating the trip to the downtown office, and its available
amenities, the likelihood of additional trips from home for errands
increases.  One home-to-work trip downtown is replaced by several
non-work trips.
     Several issues regarding the political and social aspects of
transportation planning and the impact of added capacity were
discussed.  The difficulty of considering local zoning practices
and changes in transportation modeling was one problem, considering
the economic inefficiency of local governments.  Many of the
western states use zoning by initiative, and its impacts are often
impossible to predict Most models, too, are developed around the
assumption of single-worker households optimizing their location
with regard to a single work site.  Social conditions have changed
considerably, and the two-worker household is prevalent.  It was
noted that housing prices had risen dramatically, too; and people
might be choosing their home location first, then their job
location.
     The question was raised at what level, project or areawide,
should transportation impact models be developed.  Traditionally
the areawide scale has been used but concern was expressed about
the ability of any model to address the small scale impacts of
mixed use development and the importance of the non-work trip.
     The reply was that there was a considerable amount of new
research being done on two-worker households and housing location
choice, but little had been implemented in practice.  The question
of which is chosen first, housing location or employment, is also
being studied, as is the importance of recreational opportunities
and housing location decisions.  There have been few attempts to
link these studies with the transportation models, although housing
decisions could be an important part of these models.  There has
also been recent work on business location decisions of footloose
industries, the role of telecommunications in industrial
specialization, and the breakup of firms.  Concern was expressed
for the inability to define the limits of a study area as well as
the time frame needed for a research program.  Only by setting
limits can progress be made in evaluating the impacts of added
capac-


                                                                 21





ity.  One of the problems with limits, it was suggested, was that
modeling tends to look at things that happened five or 10 years
ago.  The impacts of telecommunications are significant

at this point in time; but they will be even greater 10 years from
now and even with a considerable investment in research efforts,
the questions will continue to evolve.  Rapid changes in housing
and business location decisions, therefore, need to be considered
in modeling design.
     The comment was made that there was a distinction between
short-term research modifications and the long-term research
agenda.  There can be modifications made to short-term impact
studies that will address changing technology on a project-by-
project basis.  However, for the long-term agenda there is a lack
of understanding as to the potential impact of telecommunications. 
There is a dual problem: one dealing with the necessity for short-
term modifications and the other dealing with the long-term
understanding and incorporation of rapid changes in the models.
     It was suggested that for the short term, modeling will
continue as it is already being done; there is little that can
change the focus.  The long-term agenda is the one that the confer-
ence should be concerned with in seeking improvements to modeling
tools and understanding.  There was general agreement among par-
ticipants as to the necessity for a long-term focus on the issue
but also on encouraging the simultaneous advancement of the current
state of practice and the improvement of the state of the art in
assessing the effects of added transportation capacity.

22





Other Effects: Institutional and Financial Context

Sheldon M. Edner

     The decision-making process inherent in all aspects of
transportation planning (impact studies, transportation systems,
travel behavior issues, and land use planning) falls within the
context of organizations.  This is a concept of decision making in
more than three dimensions.  This multi-dimensional characteristic
of decision making increases the number of variables available for
travel behavior prediction.
     Those who must make the decisions or introduce them into the
transportation processes are the politicians in the urban areas
around the country.  They must make decisions regardless of the
reliability or accuracy of transportation models or knowledge of
associated issues such as business location decisions.  These
decisions are made regardless of the state of planning or modeling
practice at any one given point in time.  How does the
institutional system operate, then, in which these political and
transportation decisions are made? Implicit in this discussion, in
terms of the planning paradigm, is that regardless of how
successful the plan, the integration between transportation, land
use, and environment is critical.  The institutional legislation of
the Intermodal Surface Transportation Efficiency Act of 1991
(ISTEA) and Clean Air Act Amendments of 1990 (CAAA) has reinforced
this.  In that context, it is necessary to consider the current
organizational decision making process.
     In most urban areas the context for making transportation
capacity decisions is not an integrated process.  Indeed, most of
the institutional context is extraordinarily fragmented and, in
many areas, getting worse.  Each of the organizations within
metropolitan areas has a piece of the pie and feels driven to
implement it to their own best interest.  San Francisco is one
example of this fragmentation.  In monitoring a project for Federal
Highways, which includes the issue of how the Metropolitan
Transportation Commission (MTC) is going to react to and carry out
the new responsibilities it will have under ISTEA, major problems
have developed.  As a result, MTC has been talking to a whole new
cast of institutional characters beyond those with whom it
traditionally has dealt.  All affected participants will talk about
how to integrate not only MTC's planning function but also
operations issues such as linking together planning and operations
to produce the reduction in air emissions which is expected of the
transportation side of the equation in metropolitan areas.
     One of the most enthusiastic new institutions that MTC is
talking with is the California Highway Patrol (CHIP).  Becoming
involved in the whole process of decision making in the Bay area is
extraordinarily important to CHP because it means they finally are
given an opportunity to have some input into the design and
development of the transportation system which they must control.
     Urban areas are more and more fragmented today than ever
before.  The last decade has essentially been one in which more
diversity has emerged in the metropolitan areas with more
institutional fragmentation.  The experimentation with the private
sector involvement in joint development and privatization of trans-
portation services has created not only a larger private role but
also many more quasi-governmental and governmental agencies.  An
examination of the U.S. Census of Governments shows that the number
of governmental units across the country is increasing by
approximately 3, 000 units of government every five years.  The
primary growth takes place among special districts, the single-
purpose, uni-dimensional gov-


                                                                 23





ernmental entity with its own resource base which has
responsibility, for example, for sewers and water, in one
particular area.  The process of identifying the working relation-
ships between these organizations and what they do is more
difficult as a result of this fragmentation.
     Transportation, in the context of fragmentation, is a single
activity that must fit into a much broader set of tradeoffs that
are made by a number of organizations working simultaneously
towards their individual ends.  They do not all work together
easily.  ISTEA's Section 134 MPO requirements specifies a
coordinated metropolitan planning effort and does not even suggest
all of the necessary players.  Traditional MPOs have been
representative of general purpose governments, resulting in the
exclusion of a number of individual agencies who, in one way or
another, have been responsible for either developing part of a land
use planning process or implementing zoning, financing systems, and
other aspects of the support systems which make transportation
systems operate.
     The context of transportation is, in this institutional
environment, very fragmented.  This fragmentation has led to the
basic problems confronting many metropolitan areas and also has
contributed to the difficulty of defining induced transportation or
additional trips.  Because not all organizations share a common
definition of what constitutes a trip or trip purpose, each
organization may view an additional trip in a very different way. 
As a consequence this inconsistency makes a determination of
whether or not an additional trip is good, bad, or indifferent
Portland, Oregon, for example, is zoned for a much higher density
than the development it currently exhibits.  Those zoning plans are
already in place and have been for years.  Now that the real estate
market is growing, developers are taking advantage of the potential
for higher densities and are demolishing single family
neighborhoods and building row houses.  Residents in those areas
are concerned because they do not think the change is appropriate,
and they want to maintain the quality of life they have come to
expect.  The City of Portland's view, however, is to support the
higher density zoning opportunities.  In addition, other
jurisdictions around the metropolitan area have responsibility for
parts of the infrastructure process which are not necessarily
working in concert with the City of Portland.  As a consequence,
the whole process has become complex and people are suing one
another.  The transportation system is becoming part of that
complex process in terms of deciding where to build additional
capacity.
     In effect, there is a ripple effect out from some of the
individualized decisions.  A number of effects ripple out from
improving transportation in a corridor, such as right of way
acquisition in terms of the immediate corridor.  How far out past
the immediate corridor should impacts be considered? The whole
corridor preservation component within the current legislation is
going to test that proposition; because when an individual project
is sited, it may be obvious where to buy parcels of land for
speculative purposes.  But preserving the land for environmental
reasons may constitute the switch to a new corridor, possibly one
with a fixed guide way improvement.  Broader analysis beyond the
center point of the ultimate right of way might be required which
would involve a wider range of institutional actors with individual
responsibilities for decision making in metropolitan areas.
     Another component of the institutional context of added
transportation capacity involves tying in the operating elements. 
Over the years, operating agencies have been left out of the
transportation planning picture.  In many cases they are after-the-
fact participants.  The Tri-County Metropolitan Transportation Dis-
trict of Oregon (Tri-Met) got involved in planning for the Portland
light rail line system because they recognized, in the early
1970's, that they were going to be left to operate whatever system
was developed.  Tri-Met hired a consultant to make the case for the
system they wanted, in part, because they wanted to participate in
its ultimate operation.  Other organiza-

24





tions have not taken that kind of aggressive leadership; and, when
given the responsibility for system operation, they have not been
prepared.  This has created a circumstance where the capacity of
the system has either been degraded, or enhanced, in an unforseen
direction.
     Added capacity also raises a question of design standards.  If
land use planning is used to reinforce transportation systems so,
too, should design components in order to integrate all elements in
one overall package.  Again, the institutional context within which
that takes place is extraordinarily fragmented and continues to
remain that way.
     What has developed is a more decentralized decision system
that somehow must implement the concept behind land use planning
and its integration with transport in the environment in a holistic
fashion.  The implicit message is the sort of normative
underpinning of planning that all things should be rational and
integrated.  But, in the real world, it is not.  The institutional
decision processes are decentralized and fragmented; and, as a
result the individually pieces do not necessarily fit together.
     Non-communication occurs the most and a dynamic tension exists
between the developing suburban fringe in many metropolitan areas
and the traditional core.  The exurban fringes outside a
metropolitan jurisdictional boundary will often act independently
of one another with a tendency to create pressures to develop
transport systems to serve their perceived locational advantage. 
From a political and a broad development perspective, this fragmen-
tation tends to reinforce the notion of decentralized and
disaggregate developments that is evident around the country.  It
also begins to manifest itself in system financing, whether
transport, housing, or whatever.  The result is an incredible
amount of competition for the available financing resources within
a given metropolitan area.  The disaggregate decision system is
mirrored in the financing process.  Getting all the players to
agree on what kinds of projects ought to be built in a given
metropolitan area and to pool their resources to do so is an
extraordinarily difficult political process.  This lack of regional
cooperation leads to the situation represented in the approximately
530 individual projects that are included in the ISTEA legislation. 
Those projects exist in part because they were not funded locally
and, to circumvent local roadblocks to financing, were elevated to
the level of national crisis in order to be included in the
legislation.
     What is happening then is a disaggregate system g to pool
resources in a way that it is not prepared to do.  MPOs which have
the comprehensive oversight for developing transportation plans
have not been operating agencies or, in most cases, funding
agencies.  They have been temporary planning organizations which
have had very little institutional context or experience with long
term projects and very little authority.  As a result, they are
going to have to develop additional authority to make se collective
metropolitan decisions which to go into reinforcing the
transportation programs that need be implemented over the next few
years.
Another dimension to this disaggregated, fragmented metropolitan
institutional context s an inconsistent time horizon.  Each of the
organizations operates in its own format and time horizon, which
are often different than any other participating organization.  To
suggest t there is a difference between the transportation planning
and air quality planning process, in a technical sense, also
suggests differences in terms of timing.  Transportation plans re
built around the life expectancy of facilities, in some cases,
management systems; whereas air quality life expectancies and time
horizons are built around a different kind of context.  As a
result, there is an extraordinary difficulty in simply bringing
together that timing in a way which allows the participating
organizations to work together.  By also integrating the land use
planning process, which has an ever longer horizon in some
respects, the result is an integrated planning process with entire
frames of reference in contexts that are not necessarily
consistent.

                                                                 25





     Within all of this institutional fragmentation is the local
politics of a given metropolitan area.  Each metropolitan area has
its own unique way of doing business.  In the Portland metropolitan
area the downtown central district was preserved, unlike many other
metropolitan areas, based on a significant effort which managed to
improve the quality of the downtown.  This area is showing signs of
deterioration, however.  Competition is beginning to emerge from
suburban areas which are saying, "We gave earlier, it is our turn."
The result is a whole new set of political dynamics playing out be-
tween coalitions of downtown developers who want to reinforce the
investments made 10 or 15 years ago and the developers on the
suburban fringe who want to exploit undeveloped areas and profit
from those opportunities.  Those coalitions are dynamic and are
affected by a broad range of factors including the state of the
economy.  Unlike much of the country, Portland is a booming real
estate market and, as a consequence, is experiencing a great deal
of development.
     Other intervening issues also interact in any given
metropolitan context.  Portland has just built a convention center
but does not have a supporting convention center hotel in place. 
This development is tied to its integration with the transit system
and the rail fine, as well as being served by various highway
corridors.  Regardless of the broad general issues of concern with
regard to transportation, making that convention center work is a
key component of what is going on.  It will continue to be a key
component, at least for the City of Portland, even though there is
a proposal existing in one of the suburban counties for a new
sports arena to serve as a replacement for the downtown coliseum. 
Existing big ticket facilities tend to dictate a large part of what
goes on in a metropolitan area largely because the decisions are
made by different partners.  A justice center was built in downtown
Portland using federal highway money because the construction of an
outer belt adversely impacted a decrepit jail.  That was the basis
for the construction of an award-winning justice center funded, in
part, by the Federal Highway Administration.
     Also unique to the metropolitan context are the social issues
that exist.  The social environment of many metropolitan areas is
changing radically.  It has been suggested that it is necessary to
take into account the differences in transportation behavior in
terms of what kind of trip making decisions people make.  The
demography of Portland is a unique example.  Demographics show that
people start out as a family in the center core of the city.  When
they marry or when they reach a point of creating a household, they
tend to move to the outer areas of the city boundaries.  When they
have a family, they move out into the suburbs.  When they are done
rearing the family, they move back into downtown.  The notion that
trip making behavior over the fife of a family is going to remain
constant is also open to question.  Each metropolitan area,
depending on the character of the downtown and the overall
livability of that metropolitan area, has its own unique and
dynamic trip making behavior patterns.
     Los Angeles raises another social question with its diversity
of ethnic backgrounds.  People in the lower end of the economic
spectrum are finding it easier to afford automobiles, to a certain
extent, but are now being squeezed in an environment of intense
immigration with major impacts on schools and other social systems. 
The diversity creates even more demand on existing transportation
systems and changes the mix of social systems and social service
systems.  This will have to be a factor taken into account by
transport systems.
     The relationship between transport improvements in a given
corridor and the overall institutional context that exists in the
metropolitan area is a synthesis.  In some senses, the given, which
planners work with in developing overall transit plans for urban
areas, is the community value structure that they are trying to
enhance with the planning system.  This value system is not an
integrated whole but is put together by a number of different
institutional players in a given metropolitan area.  Recogni-

26





tion of this gave rise, in part, to ISTEA's section 134 planning
requirement that requires an MPO to provide a forum.  The process
of defining community values has not gotten any simpler or more
homogeneous over the years, even with the presence of the Section
134 requirement.  That led to part of the rationale for making the
institutional process of the MPO even more extensive in terms of
authority granted, for example, to make decisions based on the
authority to withhold federal funds.  As a result, the ability to
articulate community value on a metropolitan-wide basis and then
achieve it through planning processes drawn together in terms of
transportation and land use, is still open to question.  The
process of land use planning is made that much more difficult
because of the important question, what kind of urban form is
desired? If there is no ideal or clear cut sense of the goal, or a
holistic process of achieving it on a metropolitan level, the
efforts, in terms of siting transport systems particularly within
the context of an environmental dimensions will be much more
difficult over the long term.
     The argument can be made that a national urban policy exists
in disguise.  It appears in the context of the CAAA and ISTEA. 
This raises broad-based questions which deal with a wide range of
issues taking into account transportation and housing and
investment in a synthesizing way within the context of these two
pieces of legislation and in an institutional context of fragmented
and decentralized metropolitan areas.
     In the short term there are not going to be any Changes in the
process of transportation planning.

Open Discussion
     The discussion was initiated by a description of the
interstate substitution process as an example of a way to overcome
the inertia of competing jurisdictions.  The interstate substi-
tution process allows different areas to trade interstate freeway
segments in order for each


area to gain from the overall process and allows for financing to
be shifted from one project to another.  The process was
responsible for the development of the Portland light rail project
when over 140 other projects were combined in the process, and all
affected parties gained something.  For a substitution process to
work, individual jurisdictions need to be aware of what they would
gain by participating and, for those uninterested jurisdictions,
there needs to be incentives to encourage participation.  These
incentives can be either positive, in the form of local financing,
or negative, in the knowledge that other jurisdictions, by
participating, will have an advantage over or a negative impact on
the non-participant It was suggested that there is a limit to the
coordination of affected jurisdictions, however.  As a broader cast
of characters is required by legislation such as ISTEA and the
CAAA, making sure that all the organizations understand the
advantages of participation will be extremely important.
     Efforts have been made to broaden the geographical definition
of a city in order to incorporate a larger tax base that will
support a deteriorating inner city.  The question was then asked if
there were any similar attempts being made to increase the
dimensions of an area to include more institutions that would be
potential participants in projects adding transportation capacity. 
Mr. Edner replied that in some cases legislation may redefine
metropolitan areas.  The boundaries of an MPO will traditionally
include all urbanized areas, but it might be different from the
census definition of a metropolitan statistical area or
consolidated metropolitan statistical area.  In defining an area of
ozone nonattainment, for example, the boundaries may be different
depending on whether or not the governor of the state decides to
include nonattainment areas outside the traditional MPO boundaries. 
Some metropolitan areas might also have more  one MPO.
     There are few places with formal land use transportation
models, one participant claimed.  Often, the chosen method of
transportation forecasting involved borrowing land use forecasts

27





and simply applying different transportation scenarios.  This
method needs improvement because the link between the two elements
should be strengthened.  Land use forecasting should incorporate
transportation improvement impacts down to the local level. 
Alternative scenarios need to be developed that extend beyond
current conditions, perhaps including the impacts of transit or
transportation demand management strategies.  Various investment
circumstances and pricing changes, too, should be considered in
transportation and land use models.
     It was also suggested that the effects of the fragmented or
multiple levels of jurisdictions need to be understood as well,
regarding their impact on transportation.  One of the problems
associated with that approach is that even if all jurisdictions
within a region try to cooperate, their individual levels of
understanding will often be incompatible.  Differences in under-
standing will be compounded by different levels of financing,
analytical capacity, and data collection.  This potential conflict
presents the question of how to bring an entire metropolitan region
together with the same level of competence to approach the issue at
hand.  A related concern was, given the potential disparity between
jurisdictions, how can the EPA assure any level of overall
conformity? One suggestion was that an environmental information
system (EIS) could be implemented for the overall region to analyze
conformity on a program basis rather than on a project-by-project
basis.
     Transportation professionals, one participant contended, need
to encourage changes to the institutional structures that currently
act as impediments to planning and implementing added
transportation capacity.  Developing the data to support changing
this fragmented institutional structure will be an important part
of the research agenda recommended by the conference.  Unless
changes are made, the fragmented structure will continue to
discourage coordinated land use and transportation planning
efforts.
     One participant asked what, then, was needed to develop the 
necessary data to support changes in the institutional structure.  
It is important, one participant replied, to first look at what the 
current institutional structure had done.  A study of the Washington, 
D.C., metropolitan area that was prepared for the Transportation 
Research Board showed that in the sub-regional planning process, three 
major local jurisdictions had revised comprehensive plans that contained
inconsistent transportation and land use elements.  This example clearly
showed the extent to which non-cooperation would have significant impacts
on any future development at the regional level.  The level of
decision making needs to be equal to the level of impact.  One
solution would be to give local governments responsibility and make
them accountable for issues of consistency.  By making the
institutional framework responsible, and self-policing the
decision-making process will be more explicit and less vulnerable
to inconsistencies.
     Another point was raised concerning the difficulty in actually
defining the type of urban form that was currently in place.  How
does the existing urban form relate to the institutional structure,
and is this urban form a response to social pressures or
institutional preferences?
     An ongoing research project was described where the influences
of institutional factors on transportation and development patterns
are being considered.  In collecting an international data set and
evaluating the travel behavior differences between European
countries, an attempt is being made to identify and evaluate the
institutional factors.  Different policies of housing and business
investment also affect location and transportation decisions.  It
is necessary to stress the long-term nature of comparative
institutional research, as well as the necessity for a systematic
approach, to ensure that all key variables are identified.
     One element of institutional interactions is the concern for
system costs.  Each institution wants to select the system that
will produce the greatest benefit at the lowest cost.  To relate
this to transportation capacity, it is necessary to





consider various alternatives and the costs associated with each. 
Ultimately, the challenge of the conference is to consider how to
convey total system costs and alternatives to affected
jurisdictions and the public itself.  Fundamental to this task is
identifying the strategic options of added transportation capacity
and developing tools and models that are policy-sensitive at the
macro- and micro-system levels.


     The temporal context for the institutions which do that kind
of planning will be long term, and transportation planners are
still going to have to try and approximate it and deal with it. 
What is important is determining the relationship, over the long
term, of land use planning, environment, and transportation, and
integrating, synthesizing, and making them work holistically in a
decentralized, fragmented metropolitan area.

29





Day Two: How to Address the Problem


     The opening remarks for the second day of the conference were
presented by Dr. Gordon Shunk, Manager, Urban Analysis Program,
Texas Transportation Institute.  In his comments he restated the
original intent of the conference: to identify the principal
impacts of added transportation capacity and to determine how to
study and incorporate the impacts into models and the planning
process.  He then summarized the main points from the first day of
the conference:
-    The impacts of added capacity need to be identified before the
     modeling process can begin.
-    The principal impacts include the growth-inducing effects of
     added transportation capacity.
-    The relationship between travel, air quality, and development
     needs to be understood and incorporated into the planning process.
-    Environmental considerations need to be merged with
     transportation planning to ensure that two separate planning
     processes are not addressing the same problems.
-    Added transportation can spur development, and new development
     can cause redistribution of traffic.
-    The impacts of added capacity are conditioned by social
     changes, which greatly affect travel behavior.
-    Several questions were raised during the initial day of the
     conference and were presented for further consideration:


-    Will added transportation capacity reduce or increase
     congestion and air pollution?
-    What elements of the transportation modeling process need to
     be changed? Are the distribution mode choice and assignment
     models adequate?
-    Are there significant latent demand or induced traffic impacts
     that need to be addressed?
-    Should the development and redistribution effects of added
     capacity be considered key elements in the analysis process?
-    Does the present lack of information on latent and induced
     demand imply that these impacts are, in fact, insignificant?

The following recommendations were presented based on the
presentations and discussions from the first day:
-    It is important to consider the negative as well as positive
     impacts of added capacity in any further research.
-    More analysis of the extent of impacts needs to be conducted,
     specifically in determining spatial dimensions and timing
     (e.g., when the impacts occur and for how long)-* Better
     information on the effects of added capacity needs to be
     collected but should not be limited only to data for which
     forecasts can be conveniently developed.
-    The effects of added capacity on freight movement need to be
     part of the research agenda.
-    The effects on non-work travel and off-peak travel need to be
     considered, as well.





Environmental Effects of Added
Transportation Capacity

John H. Suhrbier


     The presentation on the environmental effects of added
transportation capacity is divided into five main sections: general
environmental concerns and issues, comments on the Clean Air Act
Amendments of 1990 (CAAA), description of a land use project in
Portland, Oregon, description of project involvement with the State
of Washington's legislative transportation committee, and comments
on the next generation of travel demand models.
     The two levels of environmental concerns are national and
local.  National environmental concerns include wetlands
degradation, hazardous waste, air quality, and climate change. 
Local environmental concerns include community character, open
space, air quality, and the not-in-my-backyard (NIMBY) phenomenon. 
The influence of both national and local concerns on public sector
decision g continues to increase in significance, and transporta-
tion professionals need to be responsive to the kinds of solutions
that are being developed in response to these concerns.  One
response is that new and expanded transportation facilities are
needed, particularly intermodal facilities.  Airports, transit
stations, and marine and freight ports need to be considered as
well as access transfer facilities.
     In order to maintain environmental credibility, existing
facilities must demonstrate maximum efficiency before proposing new
or expanded facilities.  This involves implementing such measures
as travel demand management (TDM) and, possibly, congestion
pricing.  Transportation analysts must predict the impact of these
solutions.  At a recent meeting of the National Association of
Regional Councils during a discussion of employer-based trans-
portation programs, a comment was made that these programs were not
worth discussing because they could not be analyzed by the tradi-
tional four-step demand models.  The response was that perhaps the
four-step demand process was irrelevant because it could not cope
with the policy alternatives available today.  This exchange
illustrates how important it is that the analytical capabilities of
the transportation professional be enhanced to serve the needs of
current national and state legislation.
     The traditional way of discussing the CAAA is to list the
legislative requirements.  There are, however, general analytical
requirements that need to be considered.  One analytic element is
the base year and future year emissions inventory.  Inventories in
many areas win need to be developed on a spatially and temporally
disaggregated basis.  Emissions will be examined on an hourly basis
over an entire day, which is not consistent with travel demand
approaches.  Regional vehicle miles traveled (VMT) need to be
projected on an annual basis and then the VMT projection must be
monitored.  It will also be necessary to analyze transportation
control measures (TCMs).  The CAAA also places an emphasis on
market-based economic incentives which will require analysis.
     Emissions resulting from increases in VMT or vehicle trips
will need to be monitored, requiring a new set of analysis
techniques.  How will congestion be measured, and how will it be
monitored? What is an appropriate measure of congestion on a
regional level? How will vehicle occupancy levels be measured in
response to employer trip reduction ordinances? These questions,
raised by the new air quality legislation, reinforces the need for
new analytical techniques.
     The issue of conformity and the CAAA suggests a whole new area
of analytical requirements.  The emissions levels from adopted re-
33





gional transportation plans and state transportation improvement
programs (TIPs) need to be consistent with the mobile source
emissions estimate contained in the state implementation plan
(SIP).  These are the levels against which conformity is measured. 
Conformity will be monitored at the system level, or for entire
programs, rather  a project-by-project basis.  The changes in
conformity monitoring raises several questions.  What is the cost
in time required to do a legally defensible conformity analysis?
Are existing model systems sufficiently accurate on a regional
basis, not just a CBD radial highway basis, for purposes of a
conformity analysis?
     New analytical requirements will also be necessary considering
the TCMs recommended in Section 108 of the CAAA.  These
recommendations include developing high occupancy vehicle lanes,
trip reduction ordinances, park and ride facilities, and flexible
work schedules.  How will the effectiveness of these measures be
analyzed wi the context of transportation planning? In many cases
it will not be possible to utilize the standard four-step network
analysis model sequence.  It will not be satisfactory, either, to
assume that empirical experiences from isolated analyses of TCMs
can be transferred to any other situation.
     Existing transportation models must be enhanced and new
analytical capabilities need to be developed using pivot point
analysis, elasticities, or statistical regressions based on
empirical data.  To improve existing model systems it is important
to know what variables influence highway vehicle emissions.  The
month and season is an important variable: ozone is a problem in
the summer, carbon monoxide in the winter.  Transportation
analysts, however, traditionally look at spring or fall for a
typical sample day.  The time of day is also critical, considering
the emissions impact of non-peak and non-work trips throughout the
day.  The standard measurement is VMT, but it is also important to
consider whether the emissions are from cold starts, hot starts, or
are running stabilized emissions.  Estimations of vehicle speed are
typically not very accurate in network models; and variables such
as acceleration, deceleration, and vehicle operating conditions are
often ignored.  Important vehicle characteristics to consider are
vehicle type, fuel type, vehicle age, vehicle maintenance, and
mileage.  The location of emissions, too, should be analyzed; where
emissions occur is important, whether they are in the CBD, suburb,
or elsewhere.  For example, it is customary to criticize park and
ride lots which can be effective in reducing VMT and running
emissions, but they do not necessarily reduce trip end emissions
and trip start emissions at the facility.
     A highway construction proposal in Portland, Oregon, can be
used as an illustration of the necessity for new analytical tools. 
The proposal is for a circumferential highway in the

34





southwest region west of Beaverton, extending from Interstate 5 in
the south up to Highway 26, near Hillsboro in the west This
corridor is approximately 15 miles from the Portland CBD and is
currently at the edge of the developed urban area.
     Two important aspects of Portland distinguish it from other
urban areas around the country.  First, there is strong interest in
growth management aspects and legislation.  And, second, excellent
cooperation between the environmental community and the local,
regional, and state agencies involved in transportation projects
exists.
     Two basic objectives drive this project.  The first objective
is to evaluate a set of alternatives to the proposed western
highway bypass and to coordinate this with the Oregon DOT and
Portland Metro.  The alternatives include land use actions, i.e.,
observing regional growth patterns and specific small scale
activity center developments with a focus on developing transit and
pedestrian-oriented designs.  The alternatives are also being
considered within a broadened context of transportation upgrades
for existing roads, transit facilities, travel demand management,
and bicycle and pedestrian facilities.  The second objective is to
determine the appropriate analytical tools that will be effective
within this broadened scope.  This project uses an interactive and
iterative land use transportation analysis system.  The specific
land use model is Pus DRAM/EMPAL gravity-based models.  These two
models are linked together in a model sequence with an iteration
sequence of five year intervals where the transportation results of
one iteration are used to influence the estimated distribution of
land use activities, housing, and employment in the second
iteration.
     Several products will emerge from this process including a set
of land use development and transportation proposals.  Another
product will be an advanced set of models.  By simulating the
effects of added transportation capacity on emerging development
patterns, it will be possible to consider whether there is an
alternative to new highway construction.  Finally, proposals are
frequently presented in terms of a "what if" scenario.  For
example, if a





proposed development is transit and pedestrian oriented, is new
highway construction desirable, as the land use design encourages
transit use and walking? New simulations and model enhancements
resulting from the Portland project can be used in analyzing this
of scenario.
     A recent review project for the Washington State Legislative
Transportation Commission further illustrates the need for
analytical improvements in response to environmental
considerations.  The project reviewed the methods that have been
used for programming and prioritizing transportation actions.
Washington's methodologies are considered to be among the best in
the country.  However, the review revealed several areas where
improvements should be considered.  First, the procedures need to
be responsive to a broader range of policy concerns.  Two specific
areas identified were growth management and air quality; these need
to be treated in a consistent manner.  Intermodal coordination
needs to be expanded beyond the highway programming process to
include other transportation facilities.  Investment tradeoffs need
to be examined.  One tradeoff would be between preserving existing
highway and transportation facilities as opposed to increasing
capacity.  In reviewing project alternatives, a broader range of
investment options should be considered.  Finally, these
programming and prioritization procedures needed to be modified to
respond to increased funding alternatives and increased strength in
the regional decision-making process.
     The Washington review shows a shift from the traditional
development of fixed transportation facilities plans to more
flexible alternatives that include the possibility of introducing
new technologies.  A more strategic management of existing
resources and a consideration of a variety of factors on an equal
basis, such as freight and passenger movement, open space, air
quality, and economic development has emerged.  The final
implication is that these factors must be evaluated in a
quantitative manner, not just qualitatively at the programming
stage.  To do this effectively requires analytical improvements in
transportation modeling.
     Mr. Suhrbier concluded his presentation with comments on the
next generation of travel demand models.  There have been many im-
provements to the four-step modeling process over the past few
years, particularly in its adaptation to microcomputers and graphic
technology.  However, transportation planners still use the same
four-step process with the same set of models.  This situation
presents many questions regarding travel demand models.  Is it time
to introduce some substantive improvements to the individual models
and to the way they are connected? Is it necessary to provide more
feedback from traffic assignment into mode choice distribution and
generation? Can a broader range of housing and demographic
variables be incorporated into the model structure of individual
models?
     The next generation of travel demand models might consider
expanding the range of policy sensitivity, integrating geographic
information system technology, and incorporating travel demand
management measures.  The switch to microcomputers has initiated a
decline in model standardization.  Will it be feasible to continue
to develop an overall standard model system or to concentrate on
developing a set of building blocks from which different model
systems can be developed that consider regional attributes?
Considering all these possibilities, the set of transportation and
analytical capabilities that will exist five, 10, or 15 years from
now will look very different from the standards of today.

Open Discussion
     The discussion session opened with general comments and
questions regarding the Portland, Oregon, project.  The comment was
made that the project was focusing on urban design options that
incorporated transit- and

36





pedestrian-oriented developments.  This was different from
traditional suburban development options that were exclusively
residential and encouraged automobile use.  How these design
options would blend with the existing urban fabric was being
considered in the study project.  This focus created a two-scale
project scope to look at transit- and pedestrian-oriented
developments; one project scope was macro-oriented, and the other
was micro-oriented.  One important outcome of the Portland project
was the comparisons of "visions" of future land use with model
results and the attempts to reconcile these two parts.
     One participant remarked on the difficulties presented by the
questions of scale.  Much of the land use visionary planning that
has been done at the micro-scale, for example, by Peter Calthorpe,
is not easily incorporated into conventional models.  The analysis
and literature on pedestrian-oriented developments (POD) and
transit-oriented developments (TOD) claim that lower vehicular trip
rates can result, but these studies do not answer the basic
questions presented at the conference.  One of the questions is, if
a TOD is built with neighborhood shopping, will people actually use
it; or win they drive farther to the supermarket to save 20 percent
off the neighborhood market prices? This trip might be at off-peak
hours, but it might also occur during peak hours.  How to incorpo-
rate these issues in the models is problematic.
     The question of institutional interactions in the Portland
experience was also raised.  Sections of the proposed road are
outside the metropolitan growth boundary, and there has been little
coordination between regional policy and state agencies.  Similar
issues were raised in Florida, it was noted, which resulted in
explicit revisions in the state growth management legislation
specifying that agencies had to develop plans that were part of the
entire state-coordinated planning process.
     Another participant said that the Portland proposal emphasized
the link between transportation capacity increases and travel
demand.  The study was designed with a scenario framework for
analysis which is important when considering transportation and air
quality conformity questions.  A key issue was that alternative
visions of the community needed to be considered, as the current
trends in western Portland would not be sustainable in the future. 
Alternatives to a major increase in highway capacity in the region
needed to be considered.  These alternatives incorporated increased
bicycle and pedestrian capacity in the community.  One of the
important findings of the study maybe how much TDM measures have to
affect travel prices in order to get the land use models close to
replicating the visions.
     The question was raised as to what the impacts of the Portland
proposal were and how they were going to be measured.  The main
impact would be how development would occur as a result of
alternative transportation investments in transit and highways. 
Other questions would be how that would affect the distribution of
housing opportunities and employment.  Would there be significant
variations in housing locations if transportation options were
provided?
     The key to making community scale developments work would be
the success of a community shopping facility, one participant said. 
This was one area where further research would benefit modeling
activities.  It was then suggested that another area of potential
research is housing price response to transportation investments. 
This response should be incorporated or considered in future
modeling systems.
     The question was presented regarding how transportation
capacity affects development decisions.  What, for example, are the
costs of intensification? Missing in the current models, it was
suggested, was the connection between capacity and development,
specifically, the ability to project the reaction of developers to
added capacity.
     One participant said that the focus of the development and
transportation interaction was increasingly centering on the
jobs/housing balance.  The closer people are to their jobs, the

                                                                 37





more travel can be minimized.  However, studies in Great Britain
imply that a minimum distance between housing and employment is de-
sirable; so perhaps further study of this relationship is needed.
     The discussion then focused on the need to examine the
forecasting ability of existing models.  No serious research has
been done since 1980 on the reliability of the forecasts.  Part of
the problem is the unavailability of complete historical network
data sets on which to base a study.  It was suggested that there
had never been a great deal of concern regarding model testing on a
systematic basis and understanding what the capabilities of the
model were under different circumstances.  One participant replied
that, in fact, most modelers knew of the limitations of the tools.
     It was then pointed out that one problem with modeling is that
the actual facilities being built would last for 10 to 50 years. 
How can a dynamic world be incorporated into models dealing with
long-term facilities? Fuel prices will vary drastically, as will
human values.  Twenty years ago there was little concern for
environmental issues.  For this reason, the five year iterative
approach to modeling as used in the Portland study would be
advantageous.  An example of this problem could be found in airport
planning.  It might be 10 years before an airport is built, and
then it will be in use for the next 20.  How do elasticity and fuel
prices fit into this scenario for modeling purposes? The
traditional four-step model would not be adequate for this
illustration.  Perhaps a solution would be to incorporate micro
models for short-term project impacts and then use macro models for
the long-term analysis.
     It was recommended that micro-scale planning and its effect on
trips should be one of the research recommendations from the
conference.  Specific questions should include the effect that
employment and residential micro-planning have on transportation
capacity and the effect that pedestrian-oriented development has on
capacity?
     Additional research proposals could be developed from the 1990
US.  Census data on metropolitan area journeys to work.  This data
supports research on the time element of added capacity impacts. 
Capacity improvements over 10 years for individual metropolitan
areas can be analyzed, focusing on the impacts of small area
developments.  Development types could be classified as high,
moderate, or low growth for time series analysis.  Capacity
improvements under different institutional frameworks could also be
studied.  Whether or not the local jurisdictions are amenable to
development and added transportation capacity has further
implications for modeling.
     It is important to understand who in the household works and
the location of the work place in relation to the number of total
trips made per day.  High tech industries, for example, now employ
many of the lower income workers in a family, placing them in the
overall transportation stream.  These workers may not show up on
the primary work estimation process used today.  Two people per
household that commute to work and the housing location decision
resulting from multiple commutes have impacts on the transportation
system.
     One participant then discussed the importance of not
separating transportation and development policy from forecasting
efforts.  The consequences on transportation capacity from either a
municipal growth policy, or an anti-growth policy, a high density
development policy can be significant.  The housing market is a
crucial element of growth policies.  Housing costs, proximity to
employment, and the types of potential occupants impact the
transportation network.
     The impacts of added transportation capacity, however, may be
tempered depending on what kinds of restrictive zoning or growth
management polices are in place.  Some suburbs are actually
shrinking because restrictive policies are either pushing new
development farther out on the urban fringe, or even back into the
central city.  A result of this is a lack of affordable housing in
older suburbs which are often major employment centers as well. 
Trans-

38





portation capacity improvements in these areas, then, may not have
caused increased development For this reason it is important to
look back 20 or 30 years at the relationship between capacity
additions and development.  By doing this, as well as looking into
the future at the possible influences of alternative transportation
investments and policies, the structural dynamics of the
transportation/land use system will be better understood.  To do
this, it was suggested, it will be necessary to combine micro- and
macro-scale factors into the modeling process.  One final comment
was made that a major impediment to this suggested avenue of
dynamic research was that most of the historical data collected by
MPOS, for example, no longer exist, or the computer system for
which the data were developed is no longer supported.

                                                                 39





40




Forecasting Models

Daniel Brand

     In his presentation, Daniel Brand considers the use of
transportation models in determining the effects of added
transportation capacity.  Capacity, however, is not the important
determinant of travel demand.  The most important determinant is
the change in the level of service that influences the consumer's
view which, in turn, affects travel demand.
     Rail lines are often promoted as being capable of carrying 40,
000 people per hour as opposed to 2, 000 or 3, 000 per hour on
congested expressways.  While this may be true on some rail lines
(e.g., in New York City), it is certainly not the case in other
cities.  The consumer valuation of level of service is a major
influence which affects travel.
     Added capacity has major travel impacts in high volume
corridors which are currently congested.  In large cities and in
high volume corridors, the addition of transportation capacity will
change the levels of service.  However, a capacity increase in a
high volume corridor will only cause a return to the former
congested state.  The results of this capacity increase to a high
volume corridor is greater negative air quality impacts a capacity
increase to a low volume corridor.  Development pressures, which
will be greater in a high volume corridor, account for this return
to a former state of congestion.  When congestion returns to its
former state, it can be assumed that the benefits from the trip
length increase and the increased trip frequency to higher valued
activities at the trip destinations are equal at the margins to the
added travel times and costs of those longer and more frequent
trips.  This describes the conventional derived demand benefit
assumption and presents a legitimate framework for evaluating the
user travel benefits of capacity improvements by holding constant
the assumption that marginal benefits are equal to the change in
consumer service.  User benefits, which are part of the
internalized price of travel, can be valued by allowing individual
choice behavior to be presented by the demand curve.  Individuals
place values on trips, and these can be represented by length and
mode.
     While this partial equilibrium framework is adequate for
evaluating the user benefits of added capacity, it is not adequate
for evaluating the air quality impacts, because the new equilibrium
of service is unknown.  As new development occurs and road patterns
change, there will also be changes in emission levels.
     Several points need to be made concerning congestion and
congestion equilibrium.  Congestion is increasingly out of control
in metropolitan areas.  The automobile system is a classic example
of a system where individual choice behavior is paramount.  The
private interests of the individual, who pays only for the
internalized costs of travel, is placed over those of the public or
social interests of travel.  Each time an individual drives an
automobile onto a congested system, the individual generates more
aggregate delays and air pollution for others.  In economic terms,
the marginal private cost of individual travel is significantly
less than the social cost of this same travel.
     Congestion is the price the transportation system imposes on
all users as a result of private decisions to locate in ever larger
metropolitan regions and on large plots of land at increasingly
farther distances from work.  These individual decisions do not
take into account the cost of transportation that is imposed on
everyone else.  Housing location decisions do not internalize the
cost of travel.  This leads to inefficiency, as the system loses
its ability to confront consumers with the real costs of their
decision.  This is as true in the long term for land use decisions
which generate congestion as in the short term for individual
travel decisions.  By not solving the congestion problem, private

                                                                 41





equity in housing is being threatened.
     The costs of congestion can be confronted by initiating
transportation investments such as intelligent vehicle highway
system technology which may serve to mitigate some of the added
travel and congestion impacts.  Or, consumers may have to pay later
for congestion as housing values decline with added congestion. 
For this reason, social cost questions should be considered in the
planning and modeling processes.
     Forecasting models are needed to evaluate the travel and air
quality effects of added transportation capacity.  Travel in
metropolitan areas is influenced by many factors which change over
time.  Direct observation of the effects of change in individual
causal variables is not possible, particularly in a situation where
transportation capacity is being added and growth patterns and land
uses are changing.  Multi-variable statistical techniques must be
used to separate and measure the influences of causal variables
which may affect travel and air quality.  The problem, then, is to
specify and structure these models properly.  What are the correct
models to use, adapt, and research? The data generally used to
estimate travel demand models are cross-sectional and collected at
one point in time.  These data represent a general equilibrium
supported by the assumption that people have made all of their
travel and land use adjustments in response to the levels of
service presented by available transportation alternatives.
     Travel is usually considered a derived demand commodity.  It
is desired not for its own sake but is something on which resources
must be expended in order to obtain the benefits of the activity at
the trip destination.  Therefore, the most appropriate way to
forecast a derived demand is to forecast the demand for the final
good or activity at the trip end.  The resources expended on travel
will be one of the costs of obtaining that final good or service. 
Cross-sectional data should be used when forecasting the derived
demand commodity, and the appropriate variables are the activity
patterns, not the amount of travel.
     Activity is a function of many things.  In the transportation
sector it is a function of the price and service of all competing
transportation modes that supply service to a particular area.  It
is also a function of amenities such as sewer, water availability,
schools, and neighborhoods.  The appropriate models to illustrate
this activity are general equilibrium models which include
expenditures on travel and user costs of obtaining trip-end
benefits as variables.
     One simplification of the general equilibrium model is called
a direct demand model.  This simplification converts the general
equilibrium model to a partial equilibrium model.  It incorporates
travel mode, purpose, and time period and is a function of the
price and service levels on the subject mode and on competing
modes.  While having shortcomings, the simplification process has
advantages.  One advantage is that by using existing cross-
sectional data, land use changes are modeled.
     Simplifying the general equilibrium model is a three-step
process.  First, the trip table is growth-factored based on changes
in activity levels.  These changes result from non-transportation
factors such as changes in household characteristics, size, or
lifestyle.  Then, the long run elasticities, or relationships, and
the direct demand models are used to forecast induced travel. 
These forecasts account for population replacement and the
experiences of increased use in corridors with added capacity and
improved levels of service.  They also take into account the short-
term changes in travel choices such as frequency, destination
choice, and time of day.  The third step assigns travel by mode to
the facilities g up the subject mode.
     The general equilibrium model has been used for several years
and has been called an elasticity-based method, or an incremental
method.  The incremental method has been used to forecast induced
travel which is then added to the base trip table.  The incremental
method can provide a cross check on reality and has many
advantages.  By using the cross-sectional data that are already
available, the three-step

42





process described here can provide adequate models for forecasting
the effects of added transportation capacity.


Open Discussion
     The discussion was initiated by remarks from one of the
participants regarding the request for simple transportation
models.  The comment was made that, in general, models require more 
two or three variables, especially those needed to describe
transportation control measures (TCMs).  It was felt that an issue
more important  the number of variables is that the model be
carefully structured.  The properties of the models themselves need
to be examined to verify their validity.
     A number of questions were raised regarding added capacity and
modeling.  What are the likely and most important direct and
indirect effects of the major capacity improvements? Why do these
effects occur and how are they exhibited? Development pressures and
population replacement within the affected corridors need to be
considered in model structure.  Are there additional induced trips
resulting from added capacity? Do people make longer trips or
change modes? What are the effects on air quality? It was suggested
that while partial equilibrium models are sufficient for assessing
user benefits, they are not adequate for assessing social costs
such as congestion and air quality.  A general equilibrium model is
necessary for air quality, one participant added; and conventional
models do not take into account the behavioral aspects that need to
be included.
     One participant asked which modeling practice is currently
considered to be the best.  Is it the partial equilibrium model
even though it does not allow land use impacts to be taken into
account? Also, is travel demand really derived from activities and
the demand for activities? The reply was that, first, the partial
equilibrium model is not always the best model; it would be more
convenient to use a general equilibrium model that included
forecasts, travel, and land use all in one step.  The initial
adjustment from the general equilibrium model to a partial equi-
librium model is the direct demand model, and the direct demand
model is a more logical representation of travel behavior  the
traditional trip distribution.
     The direct demand models should be considered incremental
improvements to the existing way of doing things.  They fit better 
the current sequential models that are used, but they are not meant
to be a substitute for the ultimate general equilibrium model which
forecasts travel at the immediate output of the general equilibrium
forecast of activity distributions.  These models should be
pursued.
     Another participant supported this approach and said that
given the poor quality of models which are currently being used, it
made sense to use a direct demand formulation.  The implication of
this situation is that modelers and planners need to be prepared
for changes in the modeling field as communities realize that to
test development options, new analytical tools are required.  It
was then recommended that a study of the effectiveness of the
direct demand model as used in several cities be considered as a
research project.
     The next section of the discussion centered on the research
agenda that should be considered when looking at the effects of
added capacity.  One participant strongly urged that the research
agenda be expanded.  There are many questions that the states,
MPOS, and local jurisdictions are asking, but the profession is
incapable of testing.  There are also questions being asked which
the MPOs need to be able to answer themselves, given their
increased responsibilities in transportation planning.  In the past
it was suggested that MPOs remain outside the research mode.  This
situation is changing, and it will be necessary to provide the M?Os
with the tools that will enable them to answer these questions.
     Another participant added that the application agenda is also
important.  There are tools and analytical techniques available to
provide assistance in the immediate term.  The research

                                                                 43





agenda will benefit the next generation of conformity analysis,
travel forecasters, and land use planners by providing them with
better tools; but the current application agenda should not be
ignored.
     It was then suggested that the research agenda really
consisted of two parts: shortrange and long-range research.  The
long-range agenda will consider how travel forecasting is done; but
this may not show results for 10 years, while the short-term needs
to support improvements within the next year, if possible.  Short-
term research can address immediate questions about the four-step
process.  The fact that several MPOs have experience with the four-
step process means that there is value in providing short-term
answers to obvious problems.  In the longterm, however, it is
important to look at the entire approach to travel forecasting and
consider the current context within which these questions are being
asked.  The argument was made that frequently temporary fixes to
existing techniques are accepted as substitutes for new work or new
approaches.  Also, it does not always take 10 years to implement
new approaches.  The implementation of new, shortterm improvements
to an existing model is often easier and more cost effective  the
continued use of the unaltered version.
     A request was then made to enumerate the short-term approaches
to the four-step model that had been previously mentioned.  One
suggestion was the need for accurate estimates of volumes on a link
in order to get VMT and accurate estimates of speeds on the link. 
Estimations of average speeds of traffic, which are unreliable at
this time, are needed to study emissions impact.  Variance analysis
of capacity and performance needs to be conducted.  This would
allow for better highway system link classification which would
provide a better basis for speed and delay calculations.  The
impacts of available parking and stop signs are not currently
understood.  The friction between HOV lanes and mixed traffic lanes
on a freeway are also areas that need further analysis.  Overall,
improvements to the four-step model can be made to the performance
area in regards to capacity impact.
     The next question raised was what level of forecasting should
be focused upon, precision, general or specific.  Should issues
such as specific traffic signals on local streets and pedestrian-
friendly urban design be the objective? Or, are these elements too
specific for a 20-year forecast? One participant recommended that a
general level is preferred, as the more specific forecasts will
often be too optimistic and, eventually, unrealistic.
     One participant described the speed and volume relationships
on a transportation system as chaotic.  With advances in chaos
theory and the mathematics of chaos, it was suggested that long-
range research be implemented from this viewpoint.  The
conventional four-step model would be inadequate to deal with this
approach; but real time monitoring, perhaps with aerial
photography, would be an option.  Vehicles could be observed in the
system in real time to measure volumes and speeds on . One full day
of data on a metropolitan system could be captured and compared to
the results of a four-step model.
     It was suggested that while remote sensing might be a
possibility, it moves transportation planning further away from
travel demand and behavioral approaches  ever before.  The approach
should be to understand travel behavior and household location
decisions at the household level when considering the effects of
policy variables on individuals.  The effect of parking subsidies
and its impact on travel behavior should also be considered.
     One participant then questioned the need to get to the level
of detail that would be the product of remote sensing.  While it
would be possible to gain a prediction of emissions based on
specific accelerations and decelerations on one link, the demands
on the forecasting process from conformity assessment requirements
and transportation control measure (TCM) analysis may not require
that level of accuracy.  Rather, if the transportation research
community would work with the air quality commu-

44





nity and explain the models and their limitations, a more
profitable method of dealing with emissions models and travel
variabilities could be found.
     The importance of basic research on why people make trips was
again emphasized by one participant There is still no fundamental
understanding of why people travel.  How are shopping trips
influenced by land use patterns or the availability of opportunity?
What happens when transit reaches a higher level of service? The
requirements for air quality research supports the need to analyze
these issues.
     Developers and employers also need to be considered.  Better
models of future development are needed and a behavioral approach
would be appropriate.  Future land use pattern and density modeling
will be important in generating ideas of what transportation
demands will be.  For example, most of the new dwelling units in
the Portland region over the past 10 years exhibit fundamentally
different patterns and densities those built in the previous 30
years.  Forming neighborhood clusters into villages or communities
with better patterns and densities is problematic because the
result can produce fundamentally different transportation demands 
those being currently addressed.
     Several suggestions for the research agenda were then made. 
It is necessary to be more sensitive to cost and price in
transportation models.  Most models do not even recognize the share
of employees receiving free parking.  Person trips should be the
fundamental unit of trip generation, rather than vehicle trips, to
account for total travel behavior.  It is necessary to be sensitive
to the proximity of jobs and houses and the transit system.  Access
to the transit network is important in terms of the quality of
walking and cycling, as is the ability of people to satisfy daily
needs through short trips.
     Other issues that were raised included the need to observe
existing developments and the changes taking place as a result of
land markets, transportation investments or lack of investments,
and social and behavioral factors which are reflected in household
demographics and changes.  Business location, growth and investment
cycles, and spatial elements need consideration, as well.  These
issues call for a reorganization of the fundamental data structures
used in travel demand modeling.

                                                                 45








Experimental Design

Peter Stopher

     The purpose of this presentation is to try to determine by
measurement which of the impacts of added transportation capacity
can be identified.  There are several impacts that are assumed to
take place, such as route changes, mode changes, trip timing
changes, destination changes, trip frequency, and trip chaining
changes.  These are considered short-term responses to capacity
increases.  Potentially longerterm responses include auto
ownership, residential location, employment location, and regional
growth changes.  The purpose, then, is to determine if any or all
of these variables can be measured.
     It is important to keep in mind several contextual issues. 
Given the nature of the source of these changes, a multi-year study
is necessary.  A number of these effects win not be visible unless
the phenomenon is studied over several years.  It will also be
necessary to deal with time-dependent externalities in the trans-
portation system.  It is not possible to change capacity in the
system and hold everything else constant for the next five or 10
years while it is analyzed.  Gas prices, transit fares, levels of
transit service, and other prices wi the urban area will change. 
Other capacity may be added, and some capacity might be taken away.
     As a contextual issue, planners are looking at situations
where a significant duration of congestion must exist in order to
give rise to the effects that are being studied.  There also needs
to be a fairly extensive geographic spread of the congestion.  Many
of the impacts being considered will not occur in a small urbanized
area with a localized bottleneck problem, for example, which can be
alleviated with additional capacity.  Large urban areas with
extensive congestion, both by geographic and temporal standards,
should be the study areas.
     Multiple locations need to be considered, as well.  Unless
several urbanized areas are studied simultaneously, it will not be
possible to sort out what specifically arises from the addition of
capacity.
     Three categories of experimental approaches should be
considered: the case study, attitudinal and preferential surveys,
and longitudinal panel surveys.
     An example of a case study would be the Century Freeway in Los
Angeles which is currently being constructed, or the Central Artery
in Boston which would be an actual instance of a significant
capacity increase in a very congested corridor.  The other
categories, attitudinal and preferential and longitudinal panel
surveys, are not necessarily exclusive, however.  In fact, what
should be considered is developing a way to combine several
elements of these different categories.
     The case study approach is an interesting starting point for
any sort of empirical analysis.  Obviously, a case study should
examine an actual capacity increasing project.  It is important to
identify it early enough to conduct a set of four surveys of both
residents and employers.  It is also important to include
developers within the list of those to talk with and measure
responses from.  A series of "after" surveys from the residents and
employers is needed in order to follow up on changes taking place. 
A time span of at least 10 years is required to see long-term
effects.
     The case study approach is not without problems, however. 
First there are issues which relate to sampling.  Before the
project is built, how is it determined who is likely to be the user
of that project? These users are the ones to be surveyed both in
the before and the after series.  It is often difficult to
determine who the users will be.  Some people will be users of the
corridor even before the project is built.  If some of the
assumptions about the impacts of added capacity are correct, people
should be traveling

                                                                 47





in the corridor after it has been built who were not traveling
there before.  Maybe they were not traveling at all, were traveling
somewhere else, or were going to other destinations.  How can these
users be located and the changes that take place measured?
     A second issue is time frame.  In a 10-year study, there are
all sorts of cyclical changes that go on within households.  How
can these changes be accounted for? Are they actually generated by
the changes that they themselves are going through? Would the
changes have occurred whether or not the project is built? How are
the external changes in the transportation system controlled? A
number of other changes g place within the system itself, even
within the corridor, need to be controlled if change is actually
going to be isolated.
     What about the measurement of change?  First, there is a
problem with the reliability of measuring change.  Second, it is
necessary to consider what the change is being measured relative
to.  In this case the interest is in change relative to what would
have happened if the capacity increase had not been built.  Is it
possible to find a control location which is sufficiently like the
project location chosen for added capacity so it can be determined
how much change would have taken place without the project? The
Central Artery of Boston and the Century Freeway corridor of Los
Angeles are somewhat unique in their characteristics, but it would
be difficult to find a parallel which would allow an assessment of
how much of the change can be attributed specifically to the
capacity increasing project.  Some of the work previously done, for
example, on the BART impact in San Francisco, points to a lack of
constancy in the system between the before period and the first
after-survey.  After looking at one before survey and one after-
survey, it appears that several changes have occurred within the
system in the time period.  A case study may not be an idealized
situation because of these measurement problems.  That is not to
say that a case study approach is inappropriate, but alternatives
should be considered.
     The first alternative to be considered is the attitudinal and
preferential surveys where a hypothetical situation is discussed. 
This measures how people feel they would react under this
hypothetical situation.  The target population will be people who
live in congested urbanized areas.  Questions to ask include: What
would a capacity increase in this particular corridor mean to you?
On the other hand, suppose that capacity did not increase and con-
gestion kept getting worse like it has been doing the last 10
years.  How would you respond then?
     The first place to start with this approach is a set of focus
groups who will identify exactly what should be measured.  How can
transportation planners interpret the notion of a capacity increase
or worsening congestion into language the residents and employers
in the area will understand and be able to respond to? One way is
by getting people to talk about their problems with congestion by
asking them how they might react as congestion gets worse and if
there is some way to relieve that congestion.
     The idea of a focus group, of course, is simply to help design
the main survey and decide how the survey itself should be formed. 
There are two alternatives.  One would be to conduct some simple
attitude surveys, which seem to have fallen out of vogue somewhat
but were very popular in the 1970's.  They may not be a
particularly good solution, but simple, straight forward attitude
surveys which do rankings, importances, and satisfactions should be
used.  These will potentially provide some measurement of short-
term changes and some indication of the direction of long-term
changes.  One reason for mentioning attitude surveys is because of
recent experiences with similar surveys while interviewing senior
management, particularly in the Los Angeles area.  The attitude
survey was found to be a successful technique for eliciting
information from employers which has some sound behavioral basis. 
Senior management about the future; they may even think about long-
term future, and as a result, they potentially respond very
intelli-

48





gently on attitude-type questions.
     A second set of surveys to be considered is stated preference
surveys.  There is no specific definition of the way a stated
preference should be done, but the basis for stated preference is
to provide people with alternative scenarios (either increasing
congestion or a sudden reduction in congestion) and determine,
through a tradeoff how they would respond to those changes.  Stated
preference is gaining acceptance as a method of measurement within
the transportation planning profession.  It avoids many of the
pitfalls which occur and is fairly straight forward in revealed
preference measurement where externalities exist that cannot be
controlled.  That is, in a stated preference survey the individuals
surveyed can be controlled as to the specific changes presented to
them for which reactions are desired.  The respondents can provide
the source of tradeoffs of preference necessary to find out how
their behavior would change if a congestion-relieving project were
built.
     The stated preference suggests, then, that there might also be
a testable hypothesis.  The responses people would have to a
capacity increase which relieves congestion may be, in fact, a
mirror image of the way they would respond to a continual increase
in the levels of congestion.  If there is a mirror image and it can
be tested as to whether it is a correct modeling of behavior, other
potentials are opened up in terms of ways the problem can be
studied.
     There are several pros and cons to the attitudinal and
preferential data.  The attitude and preference surveys do not
require a specific project setting nor do they involve complex
sampling issues.  The issue, however, is not to find out
specifically which residents of an area would or would not be
impacted by a particular congestion-relieving project.  Rather, it
is important to determine what the residents' current patterns of
movement are and then propose to them a relief of congestion in a
corridor they are familiar with.  This is done with complete
control of the externalities.  The focus groups can provide a basic
design, or a set of inputs, to any survey, whether attitude and
preference or case study.  The focus group can assist in helping
design the survey itself.
     There are also some negative aspects of attitude and stated
preference surveys to consider.  Attitude surveys are not reliable
for measuring behavioral intent A considerable amount of literature
exists on behavioral intent measurement and how relatively poorly
it correlates with actual behavior once the hypothetical situation
is actually implemented.  For instance, the Dial-a-Ride experiment
in upstate New York in the late 1960's and early 1970's and the
recent Metro rail ridership experiment in Miami show that there is
a relatively poor correlation between stated behavioral intent be-
fore the project is built and what actually happens afterwards.
     There are also limitations on what can be measured with
attitude surveys.  Only a certain number of concepts can be
comfortably measured with attitude surveys. little is known about
the measurement's reliability, but it is probably low with limited
quantification possible.  The attitude survey will not provide spe-
cific and quantitative data for a mathematical model which would
forecast the response size expected with a certain amount of
capacity.
     Stated preference, on the other hand, often involves a fairly
lengthy survey design or at least requires several respondents
where each one does a partial but overlapping design to keep the
design fairly short.  Much is known about stated preference in
regard to short-term measurement, however, it has not been proven
in terms of long-term reliability.  That is something yet to be
determined since planners have been using stated preference for
only a short time.  However, on the other hand, stated preference
does not require a long duration study.  A multi-year study is
still necessary but would not require a 10-year study.  An adequate
design could be accomplished over a period of, perhaps, two to four
years.
     Considering the time element, it is possible to use
longitudinal panels if there is no exclusively conflictual
methodology.  This con-

                                                                 49





siders the possibility of the reversibility of responses to
congestion versus responses to increased capacity.  An application
possibility of a longitudinal panel survey would be either in a
case study context where capacity is being increased or perhaps
under a situation of worsening congestion where the way people
adjust to worsening congestion is analyzed over a period of time.
     Both revealed preference and stated preference can be measured
with a panel.  A word of caution is necessary, because revealed
preference (i.e., what people actually do) provides measures of
changes in actual behavior.  If only one element of the
transportation system, for example, is being improved, stated
preference is not enlightening, except that it reveals something
about the stability of those stated preferences, as no other long-
term dynamic, or improvement, is occurring.  With stated prefer-
ence, different measures are considered each time the panel is
approached.  In a case study context, it is necessary to select the
panel before there is a capacity increase so a before survey can be
conducted.  Repeated measurements by the panel in the "after"
period are needed. If this is conducted under worsening congestion,
a series of panel surveys under gradually worsening congestion is
needed.
     Another consideration will be to look at pairing locations. 
One important aspect is the context within which households
operate.  The pairing takes place by considering households of
similar sized urban areas, demographics, and relationships to the
transportation system and congestion.  That enables the planner to
do pair-wise measurement, particularly if the levels of congestion
in the two locations are significantly different.  Perhaps the
congestion rate is significantly different.  It raises some very
interesting issues about the ability to measure differences among
similar groups of households under differing conditions of
congestion.
     Some strengths of panel surveys are that the panels do not
need to be inclusive of all available demographic groups. 
Intelligent sampling among demographic groups can be conducted to
obtain useful and valuable information by concentrating on certain
subgroups of the population.  Issues to deal with in any longi-
tudinal panel survey are replacement of panel members and
maintaining the interest and completion rates on surveys of panel
members, particularly if it will be necessary to go back to them
frequently for measurement.
     To conduct a panel survey wi a case study context requires a
control location.  AR that is accomplished by applying the panel to
the case study is improving the precision measurement of change within
the case study location; it still does not provide information as
to what type of change may have taken place in household behavior
if the capacity increasing project had not been built.  The panel
study and any of these studies except the stated preference, will
require comprehensive monitoring of the transportation system
performance; and not much is known about how to measure performance
in many of these instances.  Assumptions can be made as to the sort
of impact that will occur in terms of the performance on the
system; but this does not provide for the exact measurement for
that performance.  There is a challenge, therefore, as to exactly
how to monitor transportation performance in relation to any
revealed preference study which is dependent upon either worsening
congestion or a capacity increase.  The panel survey, to a large
extent, becomes much more applicable to residents  to employers,
although there is some potential to get a few motivated employers
involved in a panel.  This may have implications for future
corporate decisions, depending upon the local situation within an
urbanized area and the interest that can be created among the group
of employers to be involved in an exercise of this type.
     Having considered these three categories of measurement, it is
important to consider a comprehensive strategy which includes ele-
ments of all of these different pieces - focus groups, revealed
preference, stated preference, and longitudinal panels.  These
elements need to be combined into a comprehensive strategy

50





for an experimental design.  Specifically, a comprehensive strategy
could be developed using two longitudinal panels, one of residents
and one of employers.  The longitudinal panel of residents would
include a survey of demographics and characteristics of residents
and their households, a stated preference survey, and a multi-day
activity diary at the outset so both stated and revealed
preferences can be measured.  It would also be important to con-
tinue the panel with updates of the demographics and
characteristics of the household.  Certainly there would be repeats
of some portion or the entirety of the multi-day activity diary and
possibly some other elements of a stated preference survey which
might be conducted on a periodic basis.  Assuming that a number of
companies within the targeted urban areas would want to be
involved, a longitudinal panel of employers could be created to
conduct a survey of firm and site characteristics, undertake a
stated preference survey on the location of the firm at the preset
time, and conduct a revealed preference survey on responses to con-
gestion or to capacity increase.  Much of the work would be done
using face-to-face interviews, which are very effective and
generally inexpensive, with a sample of employers.  A comprehensive
system performance survey would be conducted each subsequent time
the panel is utilized.
     This is the beginning of a concept of an experimental design
that can be initiated and leads to a few conclusions about the
objectives of experimental design.  First, from this cursory look
at methods of measurement it is obvious that a multi-year
longitudinal study is required.  Also, a case study is not
necessarily beneficial; it may have so many complexities that it
may not serve the purposes of g to demonstrate what happens when a
capacity-increasing project is constructed.  The experimental de-
sign, however, should use multiple locations, should have
comprehensive performance measurements, and should include
employers, residents, and developers in the samples.  The design of
all surveys should be preceded with focus groups.  It seems that
the ideal would be to combine revealed and stated preference sur-
veys with the use of panels.  Longitudinal panels offer many
advantages in their precision of measurement and the types of
information that can be gained from the study.  All of this is just
a beginning, however, in forming an experimental design.


Open Discussion
     The discussion began with a question about how the focus group
and longitudinal approach would predict a change in land use as a
result of added transportation capacity.  The reply was that these
methods will provide measurements from responses by employers and
developers about how firms decide to relocate or how developers
decide to develop or redevelop an area based on changes in
transportation capacity.  These responses will not provide the
basis for mathematical models but will help answer questions such
as which changes in land use really do take place and which changes
are large enough to be concerned about.  Once significant changes
have been determined, the quantification issue can be addressed. 
The focus group, therefore, is a good starting point to find out
what people are responding to.  Is it travel time, or is it system
unreliability?
     One participant suggested that the phenomenon of change is so
complex that it would be impossible to remove it from the framework
of computer models and computer simulations.  The data from the
focus group can then be viewed as a section of the model or
simulation which can be incorporated into the whole.  The goal is
to understand the individual phenomenon and use it as a reasonable
simulation of the urban space.  Another participant agreed that
panel data can support larger models, but these models might be
very different from the traditional ones in use now.
     It was then suggested that in terms of stated preferences of
employers, it was effective to ask only that they rank, in order,
the issues

                                                                 51





related to their location or to development decisions.  There was
agreement that if a relevant issue was presented to employers, they
would be forthcoming with their concerns.  Urban area congestion is
one example of an issue that is always of concern to employers and
developers.
     The rank ordering question describes the attitudinal survey,
it was suggested.  A second question could then be asked of the
panel regarding what issues might lead individual panel members to
change where they locate or develop.  It might be tax increases or
it might be congestion.  Congestion affects the ability of a firm
to market and deliver goods, as well as its accessibility to the
employee base.  The issue of movement of goods as compared to
people is an important one.  Certain firms in a panel may be more
sensitive to goods movement and delays as compared to employee
access.
     The comment was made that it was extremely useful to do panel
surveys in a variety of cities and communities.  It was expressed
that one of the major flaws in models developed in the United
States is that data have not been collected over the last 20 years
in most communities.  The panel methodology for data collection is
a good place to focus resources to support the evaluation of added
capacity, induced travel, the effectiveness of TDM measures, and
the effect of changing urban design.
     Several comments were then made regarding the makeup of the
panel.  It is important, it was stated, to increase the size of
panel over time.  New households need to added and households that
move need to retained in the panel population.  Frequently, i was
noted, panel members were dropped soon as  move out of the region. 
It i important, however, to retain them after move in order to find
out what changes a made and how behaviors change in the location. 
The example was offered of household samples in the Netherlands
that grew from 20 municipalities to over 100 as a result of
household relocations.
     The issue of what constitutes long term regard to a long-term
panel study was raised, and the reply was that there may not be a
definitive answer.  It should be at least several years, was one
suggestion; the longer the panel is active, the more data can be
collected, which suggests that there is no definitive cut off
point, either.  The related issue of when results can be expected
to appear was then raised.  The consensus was that measurements can
be taken as soon as the second set of interviews with the panel is
conducted.  This might be as short a time period as one year if
annual surveys are conducted.  An important issue related to the
timing of results is cost, which is dependent on the number of
locations, sample size, and how many demographic groups of
households are required.
     Several observations were presented from the land development
point of view as opposed to that of the transportation planner. 
First, it is difficult for people to visualize a future condition,
especially if this condition will affect their behavior or attitude
in some way.  This presents a problem: if the change is simple, it
may be meaningless; if the change is complex, the sample population
may be unable to visualize it. A second problem is that people are
willing to provide a response as long as it does not cost them
anything.  Preferences will be forthcoming as long as a specific
cost is tied to the change.  Answers and stated preferences may be
valid only as long as there is no change; however, change does
occur and it occurs rapidly, creating problems for the validity of
panel results.
     One response to the visualization problem is video technology
used to represent alternatives and change.  This technique is being
used more frequently, and it gives the panel a conceptual sense of
the alternatives to consider.
     One participant asked whether market research organizations
could be used to provide panels and household samples for the kinds
of questions being considered regarding capacity changes.  It was
suggested that while many companies have established panels for
market research, they are expensive to access; and the respondents
are often rotated as fre-

52





quently as every three years.  Increasing the number and types of
questions presented to an existing panel causes fatigue and
influences all the responses, making the market research or-
ganizations hesitant to assume additional clients.
     The question was raised as to whether the information and
decisions based on panel data would be enough to satisfy a court. 
The answer is, probably not, the first goal of the panel, however,
was to determine which changes in capacity would be significant
enough to warrant quantification efforts.  Specific information
about the effect of added capacity should not be the entire purpose
of the panel approach.  However, after a period of 10 years, there
would probably be enough information from the panel that statements
about the effects of capacity could be supported.
     One participant asked if the panel approach was relevant to
before- and-after studies.  Considering what has been mentioned
regarding what can and cannot be measured (i.e., the reversibility
between increasing congestion and increasing capacity) the panel
approach would be relevant to these studies.  Ideally, at some
point in the future, one of the locations covered in the panel
would actually show an increase in capacity so the effect after the
addition could be studied.  An important point keep in mind,
however, is that some panel members might never be affected by the
addition of capacity.
     Several participants then made comments on case study design. 
One of the problems associated with case studies is the tendency to
focus on only one case study and assume that it is sufficient.  It
is difficult to generalize the data collected from a case study. 
The need was stressed for using a systematic case study design
involving multiple case studies.  This approach involves more 
choosing a single case or even five random cases as representative. 
Cluster analysis and the development of typologies might be useful
approaches to this problem.  There are also difficulties in doing
an adequate job of data collection.  For example, major investments
are being made in intelligent vehicle highway system () research on
real time information systems; but the majority of cities do not
keep their traffic signals timed.  Another problem is the limited
available data on parallel routes.  Identifying routes and col-
lecting these data for comparison are expensive. Conceptualizing
the data collection scheme is another problem, as is maintaining
the data over the lifetime of the project until there is something
substantial to analyze.
     An additional problem is present in before-and-after studies. 
Land development encourages long-range anticipatory development, or
that development that is spurred by the anticipation of added
capacity or new development.  The Bay Area Rapid Transit system was
discussed for 20 years before construction was started, which
encouraged this anticipatory development.  No data collection was
done that considered this phenomenon.
     Concluding comments were made that first encouraged the use of
case studies, attitudinal and preferential surveys, and longitudi-
nal panel surveys in developing a basic social science research
method to approach the question of added capacity impacts.  In
light of the larger research questions that are being asked, these
approaches should be considered to be sure they are cost effective. 
They may be only one part of a larger, long-term research agenda.
     Finally, it was suggested that the purpose of these approaches
is to gain a better understanding of reality.  Once this
understanding is developed, it will be possible to make better
estimates of travel demand.

                                                                 53








Closing Discussion
     In conclusion, the participants reiterated the major research
concerns and offered suggestions for further research.  The broad
research agenda was discussed as well as specific ideas and
possible solutions to questions raised regarding the effects of
added transportation capacity.  These suggestions were offered:
-    The overall research agenda should help quantify the exact
     nature of the known and unknown induced travel demands
     associated with increased highway capacity.  Defining
     "induced" will be important for further research and
     compliance issues.
-    There should be a focus on short-run modeling in the research
     agenda.  Geographic information systems (GIS) may be able to
     Support better forecasting procedures and should be
     considered.
-    More and better data should be collected at the metropolitan
     level.  This research will support volume delay relationships
     and some of the major inputs to air quality forecasting. 
     Historical socioeconomic data as far back as 1960 need to be
     collected to determine the effectiveness of forecasts now and
     in the future.
-    Data should be collected on non-home based travel.  The link
     between how a person arrives at work and what kind of non-
     homebased trips are conducted (during the midday, for example)
     needs to be examined.
-    New variables need to be introduced into the travel demand
     models.  The possibility of using additional demographic vari-
     ables that influence travel behavior should be researched. 
     Some suggestions include licensed drivers, vehicle ownership
     and income, and the proportion of the population living in
     multiple versus single dwelling units.
-    Some of the new variables will be difficult to forecast. 
     First, it will be necessary to determine which independent
     variables are critical to a greater understanding of the issue
     of added capacity.  When new variables have been specified,
     such as internal household details, the ability to forecast
     them accurately is the next step. * The necessity of including
     business location decisions and business logistics con-
     siderations in the research agenda was supported.  Modeling
     also needs to consider freight movement and its impact on
     transportation capacity and travel demand.
-    An effort should be made to model all trips within a
     transportation system, not only the motorized trips.  All
     household travel, including walking trips, needs to be
     addressed as do non-homebased walking trips.
-    Better models will be the result of a better understanding of
     travel behavior.  It is important to develop a model which is
     both a practical and a reasonable representation of reality.
-    The impact of inter-metropolitan travel, such as that
     generated by airports, needs to be included in the research
     agenda.  Issues that should be addressed include how many
     trips are generated to and from airports, and can this travel
     behavior be documented.
-    An effort should be made to conduct more long-range back-
     casting to determine how effective transportation and land use
     models have been.  Transferring case-specific models from one
     location to another and then testing for validity should also
     be considered.
-    Many issues of land use policy and land economics need to be
     included in future transportation models.  How can growth
     management and growth control measures be represented in
     modeling land availability and land price? A question of how
     to reflect the capitalization of transit and transportation
     investments in land use models was also raised.

                                                                 55





-    Housing preferences by demographic group, both current and
     projected, need to be included in future models.  The decline
     in real incomes in the United States will have significant
     impacts on land use and transportation in the future.
-    Better automobile ownership forecasting models that are
     sensitive to changes in the price of automobiles, income, and
     transit availability need to be developed.  The impact of
     transit stations on automobile ownership should also be
     considered.
-    A critical element in the research agenda should be the issue
     of model validation.  It is important to maintain the urban
     area database over time to be able to validate any model.
-    A suggestion was made that the research agenda be conducted in
     phases.  First, it is important to support the four-step
     process and enhance it by improving the data applied to it. 
     New elements need to be added in the areas of land use,
     freight, travel demand management, and coastal processing
     activities.  Research should also be conducted in the
     application of case studies and panel surveys.  Second, major
     modifications should then be made in the modeling system. 
     This may be a 10-year agenda item.  The third phase may be a
     complete overhaul or replacement of the four-step process.
-    The final suggestion submitted was that the environment for
     research and innovation needs to be supported because much of
     the research will take place outside the federal level.  MPOs
     and consultant studies may provide much of the suggested
     research.

56





Appendix
Conference Papers

                                                        Appendix 57








The Travel Effects of Added
Transportation Capacity

Gordon Shunk
Texas Transportation Institute

For some time transportation professionals and the community at
large have recognized that traffic fills new roadways as soon as
they are built.  The commonly held belief has been that additional
traffic was merely diverted from other facilities.  However,
transportation professionals have understood that some of that
traffic may be new, induced by the improved levels of service where
capacity was added.  This and other potential effects of added
transportation capacity have been largely ignored in the past as
insignificant, but are gaining new prominence because of their
importance for air quality assessment, congestion management, and
growth management.
     Four types of effects that result from adding transportation
capacity are especially important.  Transportation analyses should
carefully consider the possible occurrence and potential extent of
the following effects of added transportation capacity:
-    Additional Trips: New vehicle trips not made previously
     because of the difficulty or time required for travel are a
     latent demand that may be stimulated by an improved level of
     service.
-    Longer Trips: When capacity is added, speeds may increase, and
     a given trip may take less time  it had previously.  If this
     occurs, the time saved may be spent making longer trips, such
     as to a further destination.
-    Mode Shift: The possible reduction in travel time due to a
     capacity improvement may attract people that previously used
     another mode, such as transit or ridesharing, because of a
     change in travel time advantage.
-    New Development An increased potential for new development may
     result if travel times decrease.  People willing to travel
     greater distances may select residential, employment, or other
     activity locations that previously had required too much
     travel time to reach.  This may generate new development and
     longer trips.


Effects on Air Quality

     The concern with travel effects has been stimulated by the
1990 Clean Air Act Amendments which require assessing the effects
of transportation improvements on air quality.  The question being
raised is whether adding capacity is increasing, rather  reducing,
air pollution.  Current transportation planning practice generally
assumes that adding transportation capacity relieves congestion,
reduces delay, permits travel at more efficient speeds, and,
therefore, reduces air polluting emissions.
     Few (if any) existing trip generation models consider the
effects of added capacity to stimulate new travel.  The effects of
increased trip distance and mode shift may be accommodated by
current travel forecasting and growth allocation models.
     It is clear, however, from recent legal proceedings that
business-as-usual for assessing the effects of roadway improvements
on air quality will no longer be acceptable.  Future air quality
assessments will have to determine whether the potential emissions
reductions attributable to improved speeds and delay will exceed
the additional emissions reductions generated by induced traffic. 
This poses the possibility that all traditional trip generation
models, and perhaps other models as well, may need to

                                                      Appendix   59





be revised.  It is critically important to increase understanding
of the effects of added capacity on all aspects of travel and to
decide if and what improvements to forecasting procedures are
necessary in order to accurately assess the air quality effects of
added transportation capacity.


Effects on Development Patterns
     Capacity improvements may also have important effects for
development.  The added capacity may permit increased speeds and
lower travel times, enabling greater travel distances in a given
amount of time.  That, in turn, may open new areas for potential
development beyond previous limits implied by acceptable travel
times.  The effect of improved travel conditions on development
potential may be accommodated by current development allocation
models.
     New outlying developments may eventually generate longer trips
to and from currently developed areas.  Those longer trips may pro-
duce more vehicle miles of travel (VMT) which, even if traveled at
more efficient s, may produce more air polluting emissions  were
reduced by the capacity additions.
     Growth management strategies that force or permit outlying
development may have the same effect on air quality as added
capacity.  Localities implementing such strategies need to confirm
these effects to assure that their control programs are not
reinforcing potential air quality problems that may be created by
capacity improvements.
     Much of this argument is conjecture, so it is especially
important to gain a clearer understanding of the interaction of
capacity additions and growth management and their effects on
development and, in turn, the secondary effects of development on
traffic and air quality.  these issues must be carefully examined
in order to assure that the potential development and air quality
effects of adding capacity have been considered.


Effects on Traffic Congestion
     Current administration proposals for the federal
transportation reauthorization would require that states and local
communities establish congestion management programs.  The
principal goal of such programs would be to reduce motor vehicle
travel.  The potential traffic-inducing effects of capacity
improvements would appear to be counter to that goal.  Therefore,
it is important to understand how these two potentially
contradictory actions function in order to design them to work
together.
     Adding capacity could be one of the more powerful actions in
the congestion management strategy, but how congestion management
programs can make the best use of additional capacity must be
determined.  Designing effective congestion management programs
will require an accurate understanding of the nature of traffic
using improved roadways, particularly the additional travel
that may result.


Candidate Improvements
     The capacity improvements most likely to produce the kinds of
effects discussed here are new construction on new location and
major capacity additions to principal arterial roadways and
freeways.  Those major improvements seemingly have sufficient
potential to induce enough new travel to counteract the anticipated
benefits of the capacity improvement.  Major transit facility
improvements may also demonstrate the effects of interest by di-
verting traffic from roadways, thereby improving the level of
service on those roadways and inducing new traffic.


Investigative Strategy
     Careful examination is needed to identify the potential
effects of major capacity improvements and to determine why and how
those effects occur.  Such an investigation would examine the
nature and general magnitude of the hypothesized effects in order
to determine if

60   Appendix





they are sufficiently important for further, more detailed study. 
This approach will serve to increase understanding about those
impacts among the transportation profession, the affected agencies,
the respective administration, and the community at large.  Such an
approach will provide guidance for local, state, and federal
officials concerned with transportation impacts and will be a basis
for possible future action to address associated problems.
     The initial examination will be conducted by a panel of
nationally recognized professionals, experienced with the effects
of interest and with the forecasting procedures that will be
required to estimate those effects.  That panel will consider the
current state of the art and practice for understanding such
effects and will identify causes and measures of those effects. 
The panel will address the problems associated with estimating such
effects, examine the nature and severity of those problems, and
propose strategies for dealing with them.  The questions to be
addressed by the panel would include the following:
-    What kinds of transportation improvements may have the effects
     of interest?
-    What effect may be anticipated from those improvements?
-    What documented evidence is there to support or deny the
     occurrence of such effects?
-    What do we know/not know about such effects?
-    What do we need to know about effects on travel, congestion,
     air quality or development?
-    Is there a need for empirical validation of such effects and
     their causes?
-    How could such effects be estimated?
-    What problems may be encountered in obtaining those estimates?
-    What improvements may be needed in forecasting procedures to
     accommodate those effects?
     In summary, the proposed investigation should identify the
possible effects of transportation capacity improvements, which
improvements may have which effects, how those effects may occur,
how they might be forecast, and how planning and forecasting
procedures might be modified to more accurately reflect such
possible effects.

                                                      Appendix   61








Transportation Investment and Metropolitan Economic Development: A
Reconnaissance of Research Availability and Requirements

Alan E. Pisarski

Purposes
     This reconnaissance examines the research literature available
to support a study of the formative effects of transportation
investments in shaping and stimulating urban growth.  Its purpose
is to establish whether that body of literature is sufficient in
depth and scope to permit a research program to be undertaken that
would be a definitive synthesis and extension of current
understanding of the relationship between transportation facilities
investments and metropolitan growth and form.
     The primary focus of the assessment is on relatively recent,
large-scale transit investments and their formative effects.  Other
forms of investment, particularly those predominantly oriented to
passenger travel (that is, highways and aviation), are also
considered.  The interest in transit has two elements: in many
instances, a part of the rationale and justification for transit
investment lies in its presumed power to form land uses more
compactly; further, the allied case has been made for the need to
form land uses more densely in order to create more successful
markets for transit service.  In either case, the linkages between
transit investment and development need to be better understood.


Conceptual Structure
     This topic has a number of intellectual antecedents drawn from
geographic theory, sociology, logistics, and micro-and macro-
economic analyses that need to be better defined and focused in
order to make the current assessment more effective.  These are
briefly treated below:


The Formative Power of Transportation
     The most fundamental explanations of cities, their location,
scale, and growth strongly emphasize the formative power of
transportation.  Perhaps only defensibility had similar explanatory
power when large walls were still major factors in military
conflicts.  Cities often grew up around those points where
intermodal exchanges of people and goods occurred fords of rivers
and streams, confluences of rivers, end points of navigable bodies
of water, natural harbors, etc.
     In the modem era more "artificial" (i.e., man-made factors)
have played a potentially similar formative role.  For example,
railroad terminals and stations, although themselves often
determined by geographic factors, also provided options for man-
made determination of preferred locations. (Much has been made of
the power of water resupply points needed to keep locomotives
moving across America's west as a creator of towns and cities.  In
this case, towns were a product of the technologically determined
range of the locomotive.) Later, the power of urban transit
facilities and highway interchanges to open new land to development
and to focus growth have become part of the popular understanding.
     A major consideration is that in this new era, human decisions
play a far greater role than in previous times when natural
determinants were key.  This apparent power to form growth
raises social, economic, and political questions.  Public policy
becomes critical.  The forces involved - their power and
implications - need to be better understood if we are to have the
ability to control development.

                                                      Appendix   63





     Although understood, it is less clear that this power to
influence development is direct, measurable, and controllable.  The
power to control adds significant burdens to fully understand the
effects of that power.  The present study focuses on better
understanding of that power.


Documenting Economic Development -An Analogy
     One of the dilemmas among transportation professionals
regarding this subject is the lack of precision in our ability to
explain in economic terms exactly what it is that we wish to
measure and understand.  The science of economics seems to have a
rigorous structure in which these topics are treated, but none that
are fully satisfying to transportation practitioners.  Attempts to
squeeze the subject into accepted modes of economic analysis have
led to misunderstanding and confusion.
     Perhaps an analogy is appropriate to help isolate the point at
issue, if we focus on education, rather than transportation.  An
attempt to document the economic effects of education would lead in
certain predictable paths:
-    The construction of schools and colleges can be measured in
     terms of dollars spent and resources consumed.  The effects on
     the economy in terms of people employed, wages paid, materials
     used, and tax budgets can be documented to any degree of
     precision.
-    Also, the "going concern" effects can be treated.  Employment
     in the school industry can be measured: teachers, adminis-
     trators, bus drivers, etc.  Total wages, taxes paid, shares of
     the economy, etc., by the school industry are determinable. 
     Multipliers can be used to assess the further downstream
     economic effects of the monies put into the economic system.
     Neither of these perspectives is the subject of this
undertaking.  Worth knowing? Yes, but not the current topic.  Most
significantly, no public official in his right mind would use these
economic arguments to make the case for a bigger education budget,
but they are the standard basis for transportation spending
justifications.
Finally, the central matter of interest is left to be treated, and
that is education.  What difference does education make? How does
the level and nature of education in the labor force affect the
relative economic advantage of one place over another? How does it
benefit our society? Does the presence of a university and its
research facilities and faculty affect the economic power of one
place over another? How? Can we quantify these forces, and more
importantly, make them work for us?
     The hoped-for analogy here is between the thing achieved by
the education industry knowledge - and the thing achieved by the
transportation industry - mobility and accessibility.  It is not
the dollars spent in building a subway that is the subject or the
economic effects of the employment of a segment of the population
in the transit business.  Rather, it is the change wrought by the
power of transit to provide segments of the population with access
to certain places differentially or its ability to raise the
ambient level of mobility for everyone.  To understand that and to
quantify it is the purpose.  It answers the question: What is
transportation worth?

Redistribution Versus Growth
     One issue that causes confusion and argument concerning
development effects of transportation investments is the
distinction between real, newly-created development effects of in-
vestments and merely redistributed development. There are two
elements to this issue that warrant discussion.
     First, the conflict over new versus redistributed development
contains elements of circular reasoning.  It is somewhat dependent
on the eye of the beholder, i.e., the span of ownership or
jurisdiction of those affected by the change.  The geographic
location of the site for development will be redistributive or new
depending on the geographic range of competing

64   Appendix





alternative sites.  If a new baseball stadium is located in the
north of a county instead of the south, it will be "new" for the
northern part of the county.  It might be seen as redistributive in
the county if there was no issue of possible location outside the
county.  In the region at large it most likely would be seen as
redistributive.  Nationally, it would be a zero-sum game - a gain
in one place versus an equal loss somewhere else - with no likely
significance.
     If a metropolitan area is competing with other areas for a
ball team or an assembly plant, its selection as the site is a new
development to the area.  Again, the state might see this as merely
redistributive if all the alternative sites were within the state.
     Ultimately, one might see even national trade consequences as
mere redistributions between the U.S. and its foreign competitors
in a global sense.  "New" then would exclusively mean adding to the
world's gross product.  It must be recognized that fortunes are
made and lost by mere redistributions of economic activities and
that every redistribution has both real and new economic
consequences for someone.
     The second element is that in some cases redistribution may be
the goal.  The location of transport facilities in order to
redistribute activities, to change the density of development, and
to re-aggregate certain land uses, may be a conscious policy or
intent of a development plan.  In this case the issue is not on the
competition of who is to be the beneficiary of new development, but
rather the net overall benefits expected from redistribution.  In
the baseball example, the placement of the stadium in the northern
segment of the county may be a matter of interest to public policy
because of the county's interest in concentrating development in
that area or avoiding other areas because of environmental concerns
or traffic conflicts, rather  any concern about locational competition.
     This second point raises key issues for the transportation
profession.  Public policy may focus on mere redistribution but
must recognize that its policies are creating winners and losers. 
Public policy generates real, new economic effects on someone. 
Also, beyond economic winners and losers as the result of siting
choices, the conscious redistribution of land uses into differing
configurations and densities causes very broad, only partially
understood, social and economic effects on residents, employers,
and visitors that go well beyond the public service costs involved. 
These must be better understood and more fully incorporated into
the calculus of the effects of land use policy choices.


New Economic Realities
     The classic concepts that have guided urban theory make
extensive use of the power of logistics costs in affecting human
settlements, as noted earlier.  This focus is fundamentally
oriented to the movement of goods and resources rather than the
movement of people.  Two sets of questions arise:
-    What about the movement of people: How does this affect urban
     development? Are goods movements really more important? What
     about just-in-time for people? Is raising the general level of
     ambient mobility in a region a significant factor in at-
     tracting new development or retaining it? Does it
     contribute to regional comparative economic advantage? What
     about the power of new investment in an already mobility-rich
     environment? Can it still have significant land-forming power?
-    What about the new economic structure of contemporary society
     with its orientation towards services, marketing, high value
     goods, high speed delivery systems, etc.? How does this affect
     the power of transportation to influence development?
     Classical logistics arguments seem to be highly dependent on
     industrially-linked economies, with their focus on coal and
     steel flows, etc.  What is their utility in a post-industrial
     society? Industrial logistics theory explained Pittsburgh,
     Detroit, 

                                                      Appendix   65





and Chicago.  Are new theories or new applications of old theories
required to explain Orlando, Phoenix, and San Jose? A useful
research effort in this area must be responsive to these areas of
concern.


Background and Literature Review
     The first difficulty in treating this subject area is in
knowing what to call it.  At least part of the research problem of
the transportation sector in this area is the lack of a shared
terminology for the matters of interest.  The literature review can
range over the topics of economic development, land-use
development, impact analysis, efficiency studies, metropolitan
planning, and modeling, but extends much further into sociological,
geographic, and economic literature.  A number of studies provide
extensive listings and reviews of some of the diverse literature
available.  Many of these studies discuss this same concern for a
better terminology with which to structure these investigations.
     Further problems evolve from the unclear character of the
economic effects that are being studied.  The general tendency has
often been to focus on the impacts of the expenditures made on
transportation facilities or the effects of economic activities
that go on within these facilities rather  the economic influences
that flow from the mobility and accessibility benefits provided by
the investment in these facilities.  These are variously divided
into direct, indirect, or induced influences or into primary and
secondary impacts (McLeod, PIAT).
     A branch of the topic raises interesting issues of
perspective.  Rather than examining the economic effects of
prospective investments as an impacts issue, a DOT study looks at
transportation investments as potential tools in a development
strategy for a community intent on achieving economic development
expansion (National Council for Urban Economic Development).  This
study raises important questions about the cost-effectiveness of
using transport investment as a tool of economic development
strategies.  Much of the European experience would fall into this
category.
     The Transportation Research Board Williamsburg Conference on
Economic Development raised many of these same issues.  Its report
will be very valuable to this subject.  A paper presented treats
the important questions of the influence of transportation
investment in the new economic environment (Bell).  The paper makes
the key observation that transportation bottlenecks are still
crucial in that current industries may be just as dependent on
effective transportation as those in the past (e.g., American
Express versus U.S. Steel), but the new industry is more flexible
in that it is more able to relocate in search of improved mobility
or other amenities.  First, it is leaving only office space behind
rather  an immense investment in facilities; second, its needs are
more generally available: a good airport, good general local
mobility, and good highway access versus a port of required depth,
double-track rail yards, etc. (the recent move of AAA from
Washington to Florida is instructive).
     Part of the problem is that the purposes of many of the
analyses performed as general studies or specific project studies
vary considerably and, thus, modify the scope and rigor of
undertakings.  Many such studies are promotional in nature, intent
on maximizing expected positive effects to attract investors or
public support, which affects both their validity and their
utility.  Such studies rarely exhibit an interest in retrospective
tests of the original assertions concerning prospective impacts and
are of little value.  Only the major before and after studies of
transit properties and a few others have been effective in
overcoming these weaknesses.


Transit Studies
     The dominant efforts in transit studies are those that
centered around the building of the major rail rapid transit
systems in the San Francisco, Washington, D.C., and Atlanta areas
(Rail Transit Impact Studies, DOT).  These were generally large
scale, extensively funded, multiyear efforts that expressly
incorporated a be-

66   Appendix





fore-and-after format.  In each case, particularly in San Francisco
and Washington, D.C., an extensive body of literature was developed
over several years.  Only the Bay Area Rapid Transit System (BART)
study came to a defined conclusion.  Washington, D.C. Metro and
BART began ambitiously but slowly faded due to a lack of sustained
financial support.  In many respects these were ground-breaking
efforts developing new methods and new perspectives on the
character of transit impacts.  In several instances this work has
been expanded on and added to over the years since the major
efforts concluded.
     A question can be raised as to why heavy focus was placed on
impacts analysis in the transit sector without similar concern for
before and after treatment in the highway and air sectors.  There
are several possible explanations:
-    Transit undertakings were very large scale in dollar terms and
     their supporting demand was primarily prospective.  Scrutiny
     was, therefore, extensive.
-    Transit undertakings were system development events rather 
     simply single facility development efforts.  Their prospective
     effects were, therefore, regionwide.
-    Transit undertakings came at a time when concerns about the
     impacts of public investments, both positive and negative,
     were very high.  The trend of the times was to do large scale
     studies as we learned how to treat these questions.  For
     instance, the Metropolitan Atlanta Rapid Transit Authority
     (MARTA) program in Atlanta conducted the first system-wide
     environmental impact study.
-    Part of the rationale and justification of these facilities
     and other transit undertakings were based on prospective
     development effects and influences on urban form.  It was
     appropriate to assess their effectiveness in achieving those
     ends by studying their after-effects.  Many saw these early
     undertakings as the first of a large number of prospective
     heavy rail building programs in other cities to follow.  Their
     success or failure in justifying themselves on the grounds of
     influencing development trends would be a significant factor
     in making the case for the entire national program.


BART Impact
     The BART Impact study program was a major comprehensive study
of the effects of the Bay Area Rapid Transit system as it developed
in the San Francisco area in 1972-1974.  The impact study was
organized in 1972 under federal auspices and completed in 1978,
about five years after the inauguration of BART service.
     Two elements of the study are pertinent to the current
research: "Land Use and Urban Development Impacts of BART, " April
1979 and "The Impact of BART on Economics and Finance, " December 1979.
     The major BART findings established the baseline for studies
of transit land development impacts conducted later.  The study
established that BART's greatest strength was in generating
advantage for long distance suburban-to-center trips with
particular emphasis on weekday peak-period travel, more like a
commuter rail system than a traditional subway system.  Overall,
the fundamental finding in regard to land development was that BART
has affected land uses only when supportive conditions - such as
zoning provisions, community support, and market demand - are
present.  In the absence of a supportive environment for land-use
changes, the system has had little influence." In some cases its
effect was that of". . . coalescing anti-development sentiment in
the communities.  BART has not reversed declining market trends or
initiated developments in areas where demand for new developments
are absent." It was found that BART's most notable impacts were in
the downtown Market Street area.  The influence was seen as more
indirect than direct.  Other key points were:
-    Ridership and other effects were less than expected, primarily
     because final system

                                                      Appendix   67





     service levels were considerably less than planned.
-    The economic growth of the area as a whole has not been
     affected by BART.  "BART generated very little of the major
     regional economic benefits expected by its proponents."
-    The system has encouraged a city-centered concentration of
     activities and it has provided access to a larger work force
     in its service area.
-    BART played a limited role in new suburban development. 
     Employees seemed to consider BART's availability in evaluating
     employment options but employers' location decisions seemed
     little affected by BART's service availability.
-    There is no evidence that BART had a permanent impact on
     property prices or rents.
-    "It is too early to determine what BART's ultimate impacts
     might be."
Discussions with MTC staff indicate that little is currently being
done in the area of BART assessment.  The recent fifteenth
anniversary of the system generated only anecdotal retrospective
material (Markowitz).


Metro Impact
     The Metro Impact study covered an array of impacts of the new
transit system from 1976 to 1985.  Most of the study was focused
from 1976 to 1982 which is too short term for assessing development
changes.  Early development impact analyses identified substantial
growth in new floor space in almost all land use categories around
Metro stations.  About half of regional commercial floor space from
1979 to 1982 was within a 15-minute walk of a Metro station.  The
density of stations in the city center was such that almost any
construction in the core area - downtown Washington, D.C., and Ar-
lington-would fall within a 15-minute radius.  In the suburbs,
however, about 30 percent of commercial development occurred around
Metro stations.  Those activities most oriented to station areas
were offices, hotels, and mixed-use facilities.  Projects around
Metro stations tended to be twice the size in dollar terms as those
built away from Metro station areas.
     More recently, an employment study for the period of 1980 to
1985 was conducted.  This study used the full 103-mile system as
its base for station impacts even though some of them are still not
open.  This study portrayed a negative image regarding transit's
power to change development It noted that while employment in the
five-year period grew by 15 percent in the region as a whole, it
grew by less 7 percent within Metro station areas.  All employment
sectors exhibited similar patterns.  The emergence of suburban
activity centers, the build-out of some station areas, or the shift
to service and trade employment were considered possible
explanations for this trend.  At the same time, Metrorail stations
captured 43 percent of the region's commercial development between
1980 and 1986.  The Washington, D.C., Metro Impact studies
concluded with interesting and useful work in commercial
development trends, employment trends, and changes in accessibility
but with no definitive conclusions regarding Metro's economic
development impact.
     Washington, D.C., COG continues to maintain the non-
residential construction activity data files that permit it to
document metrorelated development activities on a quarterly basis. 
The first quarter 1990 report indicated that metro stations were
significant development attractors with 40 percent of new develop-
ment around stations.
     It is to be noted that COG is currently awaiting UMTA/WMATA
funding for an update of Metro development trends.  It will also
survey work at MARTA, BART, Baltimore, Quebec, and Toronto as part
of its assessment.  This could provide a major opportunity for
extending past impact analyses.


MARTA Impact
     Atlanta is a city for which transportation has been a central
development force.  The original genesis of the city was derived
from major railroads coming together.  Later, the

68   Appendix





conscious development of its airport as a major hub helped make
Atlanta the major regional center in the South.  Its freeway
systems were used to support its central role.  Thus, the devel-
opment of a transit system arose in an environment that understood
and appreciated the formative role of transportation.
     The development of the MARTA rail system has generally been
given credit for arising from the best planning environment of the
various before-and-after studies (Davis, Meyer, Price, Cambridge
Systematics).  Focus of that planning environment was on the
station areas' planning and the monitoring of developments around
stations.  With UMTA assistance, a series of Transit Station Area
Development Studies were performed.  these were cooperative efforts
between the Atlanta Regional Commission, Georgia DOT, MARTA, and
the cognizant local government to minimize traffic impacts and
maximize development opportunities around stations (Price).  A
Transit Impact Monitoring Program was developed to evaluate trends
over time and establish the extent to which the plans were being
implemented.  Five station categories were developed for monitoring
purposes: high intensity urban, mixed use regional, commuter, -
community center, and neighborhood.
     The MARTA rail system was originally approved by voter
referendum in 1971.  The first phase of the system, the East Line,
opened in 1979.  Overall, 53 miles of the system with 41 stations
are planned.  A key factor is that about 65 percent of the system
operates on existing rail right-of-way.
     The land development effects of the MARTA system are open to
debate.  Some studies have focused on those areas where development
has indeed occurred, accepting any development near a station as
"rail-related." The Davis study, based on 1985 data, argues that
rail transit projects are too expensive "to justify them solely on
their merits as transportation systems." Development effects thus
become crucial "as a means of justifying these systems based upon
the additional economic benefits they can potentially generate."
The focus of their research is on "joint development, " meaning
joint public-private development linked to transport
infrastructure.  The study confirmed previous findings that devel-
opment around rail stations "occurs in conjunction with a strong
market situation and supportive zoning policies" (Davis).
     A study benefiting from reviewing development in a later time
period occurred in late 1988 as a part of an assessment of UMTA
programs using case studies (Cambridge Systematics).  This study is
more elaborate than previous efforts.  Rather  simply tallying con-
struction in a service area around stations, the study examines the
history and behavior of the individual projects.  Its findings
regarding development impacts in Atlanta, based on extensive
interviews, are at best mixed.  Given the axiom that transportation
is a necessary but not sufficient factor in land development, it is
unclear that transit falls into the necessary category.  Parallel
sites are shown to have developed similarly close to and distant
from station areas.  Overall, their finding is that "case studies
furnish no evidence that rail transit has shaped regional land use"
and ". . . has shown mixed and/or modest evidence of rail transit's
ability to shape development near downtown and other commercial
stations locations." Specifically, the report states "in Atlanta
the evidence for this kind of development is incidental."
     A number of downtown development complexes, such as the
Georgia-Pacific, Southern Bell, and IBM headquarters are closely
examined and the concept that MARTA can be credited with their
location is evaluated.  In all cases the finding was that these
structures were highly oriented to the CBD and the predominant
orientation of the tenants was to the auto.  They cite that
developers use the presence of transit as a rationale for project
densities in excess of common densities prevailing which " may be
causing as many problems as they are solving."
     In Atlanta, the current effects of MARTA are open to question
concerning their power to

                                                      Appendix   69





form urban patterns or attract development.  The most recent
regional plan was revised to reflect the failure to sustain the
center's role in development and to respond to the rapid
suburbanization of jobs to the north.  As in BART, the sense of
disappointment and naivete regarding the planners' expectations
regarding the formative power of transit is clearly evident.


Smaller Scale Transit Programs
     More recent transit investment programs have been less
extensive in both absolute and relative scale and, thus, less
potent in their ability to form metropolitan land patterns
(Emerson).  The San Diego light rail system makes no pretense of
attempting to form development given its location and structure
(UMTA, Transit Impact Studies).  Even the larger scale Los Angeles
program will have little significance on a portion of the region's
activities given the immense scale of the area.
     Smaller scale activities such as light rail developments may
still be significant in terms of the scale of the communities
(e.g., Portland, Sacramento, Buffalo, etc.) in which they are
developed (Arrington, Paaswell, CATS).  Reports from Portland point
to significant land development effects (Affington), whereas early
Buffalo impacts appear negligible.  However, more recent anecdotal
Buffalo experience points to significant resurgence in the downtown
area.  The most typical area of concern is the power of transit to
support and sustain the downtown area's influence.  In Buffalo, the
issue may have been a trade-off between overall regional service
and supporting downtown development.  An Urban Land Institute (ULI)
study conducted in the early stages of urban transit development
identified the factors affecting downtown development and the
industries most affected (Black).  New programs in Baltimore and
Denver would be appropriate for study of economic development
trends from the start of a project, especially downtown.
     The foregoing indicates the lack of an appropriate metric for
determining the characteristics for significant transit land
development impacts.  Among the factors are:
-    Absolute scale.  The absolute dollar volumes involved, or the
     absolute number of people affected by a new project, could
     define the basis for impacts assessment.
-    Relative scale.  A key may simply be the prospective share of
     the region's persons or trips impacted by the investment.  A
     light rail system cannot have the same effects in Los Angeles
     as in Tucson.  This might be expressible in terms of the share
     of total transport investments in the community represented by
     the transit undertaking or by the change in the ambient levels
     of accessibility generated by the new facility.
-    Pace of development.  The rate at which new population and new
     jobs are being added in a community affects the ability to
     change historical patterns. ff the goal is to change land use
     by the year 2010 a key question would be what percent of 2010
     land development is already on the ground? In areas of the
     west and south, where annual growth rates are triple and
     quadruple that of the national average, the opportunities to
     guide or deflect ultimate patterns will be greater; although
     those areas are typically the least susceptible to high
     density patterns.  The reverse issue is raised regarding the
     ability to use transit to turn around a declining area and to
     generate growth.
     A number of studies have surveyed the impact analyses
performed in varying cities with a mixed set of reactions, neither
uniformly positive or negative (Emerson, Meyer, Cervero, DOT). 
Many point out the need for other factors to be present in order
for transit influences to be effective.  Factors such as supportive
zoning, land assembly potential, overall growth rates, and other
supportive public policies are identified.  These factors could
overwhelm the transit investment's influence.  In some cases public
policy might create a self-fulfilling prophecy for the expected
development effects by

70   Appendix





replicating the thinking of private developers and going where they
were going anyway - a similar argument could be made for parking
garages.  Or, by consciously siting public facilities at the
transit investment sites, public agencies might directly cause the
effect they were trying to create.  Particularly, special zoning
bonuses around transit stations as in BART might be sufficient to
redirect development to those sites even without the associated
transit investment.
     With all of the myriad factors involved and the many disparate
interests at stake, it is not surprising that conflicting evidence
exists.  It could be productive to revisit past studies to update
findings and to research new modes of studying the effects of
investments in new social and economic contexts and in new metro-
politan environments.


Highway Studies
     Highway impact studies of the 1950's and 1960's are
conceptually closer to the transit studies of the early 1980's than
they are to later highway studies.  Like many of the later transit
studies, they were often prospective in nature, seeking to help
justify the investment in the facility by extensive description of
the economic benefits to be produced (BPR). Land development
effects were most often concerned with specific changes along the
right-of-way as a result of construction. This is consistent with
the time period. In many instances, freeways were new ideas; and
the need to gain public support was critical to convince people of
the value of freeways in advance (State University; FHWA, Impact of
Beltways).  Rather sophisticated, high caliber work was done in
this period referencing contemporary sociological and ecological
research (BPR, State University).
     By the 1970's the highway impact studies had changed to a more
passive ameliorative tone.  The emphasis shifted to minimizing the
negative consequences of road development rather than accentuating
their positive effects.  It almost appears that the positive
economic effects needed no further justification or support; rather
the critical issue was overcoming negative environmental and social
concerns.  Noise and air pollution and the need to avoid land use
disruptions are significant concerns (FHWA, Social and Economic
Effects 72, 76).
     In more recent times, the pendulum has shifted back to
economics.  This proceeds from the shift to alternative funding
sources in some instances and also in response to the nationally
recognized need to expand our productivity and competitiveness in
the world scene.  Two trends are evident.  First, the macroeconomic
case for highway investment is made based on national economic
relationships.  These studies seek to identify broad relationships
between levels of infrastructure expenditure and levels of the
economy (FHWA, current literature).  These studies are not
facility-specific analyses.  The work described by Politano is a
hybrid using Bureau of Economic Analysis multipliers to estimate
economic effects of highway system plans that expressly include
operating cost changes resulting from system development.  The
second trend is evidenced by specific facility studies often
related to facilities aimed at filling in gaps in the interstate
system, shortening paths between key points, adding better access
for rural development, or adding capacity in congested corridors
(Illinois/Missouri DOTS, Wisconsin DOT).
     Traditional weaknesses in these studies that need to be
overcome relate to the tendency to make the macroeconomic case for
highways based on the jobs involved in their construction and
operation or their general economic role (Pisarski).  In the
facility-specific case, the studies increasingly recognize and
attempt to quantify the critical economic benefits from improve-
ments in mobility and accessibility (Wisconsin DOT, Indiana DOT). 
This work needs expansion.


Airport Studies
     In many respects, patterns in assessing airport impacts are
very similar to those noted above for highways.  In the early years
after World War II, needs were analyzed extensively

                                                      Appendix   71





and airports were built.  Studies focused on beneficial economic
effects.  Later the assessments became defensive, like highways,
based similarly on noise and air pollution concerns and
particularly on negative land use conflicts with adjacent
properties.
     Recent studies stress the economic importance of airports
based on traditional justification methods - jobs involved,
revenues produced, taxes generated, etc.  The Federal Aviation
Administration (FAA) has developed a standardized procedure for
airport economic impact assessments.  The RIMS II model of the
Department of Commerce has been modified and used in a Texas
highway assessment (FHWA, current literature).  This approach would
seem to be equally applicable to transit or highways but is most
prevalent in aviation.  The approach is prevalent in aviation
perhaps because airports are single sites and more individual,
private concern exists than for transit facilities of highways. 
Over 100 such studies have been done (PIAT).  The process has been
turned into a cookbook activity that tends to inflate the real
benefits of aviation.  These standardized procedures do not provide
significantly useful products to this study.  A recent study
produced by the Partnership for Improved Air Travel (PIAT) does
differentiate these efforts from aviation efficiency studies that
consider true travel benefits in a cost/benefit framework, which is
closer to the realm of current interest.
     Unlike highways or transit, little work seems to have been
done in aviation outside very traditional economic impact studies
with respect to the effects on development. Research outside
government and the operating industry has treated this subject and
demonstrated the immense formative role aviation service may have
in metropolitan development in the 1990's (Schweiterman, Irwin). 
One aspect of the aviation picture which may help explain this
surprising lack of research activity is that mobility patterns to
and from a given city can change dramatically, independent of
changes in the physical character of the facilities involved.  The
shift to hubbing is one example.  For instance, a review of the top
50 metropolitan areas in America shows that several hub cities
(i.e, Chicago, Atlanta, Dallas) have direct access to almost all of
the top 50 areas; whereas other cities of similar population have
far more limited access.  In the case of smaller cities, an area
such as Toledo has access to only 10 of the top 50 areas, while the
minihub at Dayton, a city of comparable size to Toledo enjoys far
greater direct access to 27 of the 50 cities (Schweiteninan).  This
must affect their relative attractiveness to certain kinds of
industries and activities.
     In a forthcoming study, changes in air access in a given city
is shown to be linked with the growth in certain service-based
industries (Irwin).  This provides an important starting point for
analyzing the contribution of air service to a region's comparative
economic advantage.


Transportation Research Board Possible Tasks

     The following task descriptions provide a broad array of
useful research opportunities associated with this question.  They
represent a fairly broad attack on the economic development effects
of transportation investments focused on passenger travel
investments in the individual modal areas.
     It is clear that most of these research tasks are not
appropriate for a TRB research undertaking.  While there is a great
deal of literature available on the general subject, most of it is
of a survey character.  There is little that provides solid primary
data that could contribute to a serious study.  Rather  a grand
global effort, small, focused studies producing tangible
contributions to the subject area in specific delimited areas seem
most appropriate.  Most such work would best be performed by the
responsible agencies within the metropolitan areas being studied or
in academic environments.
     This is an important area, made more important by current
concerns regarding national legislation.  There are ways in which
TRB

72   Appendix





can make a contribution in each of these areas.  These areas have
been identified within the detailed discussions of the following
possible research tasks.  There is so much research work being
conducted in the general area of economic development and
transportation investment that it would be appropriate for TRB to
play a role in screening and coordinating these research
activities.


Task 1: Update and Expand Literature Review
     This reconnaissance has sought to identify the available
literature in this topical area.  The materials identified are
presented in Appendix A. If a TRB-sponsored research effort is to
be undertaken, the researchers should review the materials
identified in Appendix A and expand their research to materials not
contained there.  Other resources may be available.  The literature
in this area is variously labeled and has no clear structure or
bounds.  Some of the literature falls into the areas of economic
development, land use, impact analysis, urban planning modeling,
and feasibility studies literature.  The fields of geography and
sociology also have important potential contributions.  A number of
the references contain excellent bibliographies.  To avoid
redundancy, bibliographies were not reproduced.
The following areas need further exploration:
-    Continued compilation of on-going assessment efforts by the
     major impact study area cities - The Bay Area, Washington,
     D.C., and Atlanta.
-    Limited or anecdotal efforts by metropolitan areas with
     smaller transit undertakings - Detroit, Baltimore, Miami,
     Sacramento, etc.
-    Pertinent foreign experience, most notably the Canadian
     experience with Vancouver, Calgary, Edmonton, and Toronto and
     experience in Asia and Europe as well.  The experience of
     Lille in France, an apparently successful effort to stimulate
     development in a declining area, would be a useful counterpoint
     to the Buffalo and Detroit transit programs.
-    Private sector literature can be a very effective resource. 
     The products of the Urban Land Institute and the National
     Council for Urban Economic Development are effective
     resources, but many other private associations focusing on
     developer interests, parking interests, and shopping center
     interests could be of value.  The literature and data sets
     concerning land tax and assessment experience around transport
     investment properties is an open area for research.


Task 2. Assessment of Transit Development Impacts
     Within this task a number of avenues of investigation need to
be pursued relating to transit investments in the United States. 
The sub-tasks to be pursued are:
     Task 2A: Revisit and review major impact studies.  Through the
1970's and 1980's a series of before-and-after studies were con-
ducted in areas where our major transit investments occurred: San
Francisco, Washington, D.C., and Atlanta.  A major body of
literature was produced.  One of the realities of the studies was
that it is difficult to assess development effects, which are
necessarily longer term in character, early after system
development The last of the systematic national reviews was con-
ducted in 1982.  Only the BART study was fully completed.  Now,
almost 10 years later it would be timely to revisit these programs
to assess whether the longer-term effects are more tangible today.
     A number of approaches can be considered.  First, local
planning agencies should conduct retrospective assessments. 
Second, the current COG activity, "Development-related transit
ridership potential at future metro rail stations,  to be funded by
UMTA, could be the nucleus for such a retrospective effort.  This
activity could be expanded to be more comprehensive. TRB could
provide review, synthesis, and

                                                      Appendix   73





coordination.  A conference could be held to bring researchers
together to discuss goals and methods or an expert panel could be
formed to monitor the COG activity and to review different
approaches for other researchers.
     Task 2B: Review of new smaller scale investments.  A shift in
emphasis to smaller scale transit programs occurred in the 1980's. 
The ability of transit programs to stimulate or guide development
is diminished by their small scale.  It is less appropriate to
expect significant land-use shifts associated with these activities
but an assessment is still worthwhile.  A review of current
experience regarding the land development effects of these programs
could be of value.  One important contribution of such a study
might be to establish guidelines for small scale assessments based
on relationships in area size, project size, etc.  Areas of
pertinent application include Buffalo, Portland, San Diego,
Sacramento, Miami, and Detroit.  Useful comparisons would be
Vancouver, Calgary, and Edmonton.
     As noted, the proposed COG effort will survey some of these
same cities.  This could provide the basis for an expanded
understanding in this area.  Otherwise, the available literature
would not support a research effort of smaller transit projects at
this time.


Research Questions
     A review of the transit impact literature leads to the
following questions:
1.   Does ambient accessibility represent a significant factor in
     comparative advantage among cities?
2.   Can scale effects be identified in the effects of transit or
     other transportation investment on development? Are they
     relative or absolute? What are the best statistical measures
     or indicators of these scale effects?
3.   Is there any evidence of the ability of transit investments or
     other transportation investments to turn around a declining
     metropolitan situation?
4.   What are the key factors governing development or the lack of
     it around transit stations? Can the elements involved be
     quantitatively described?
5.   What is the power of transit investment to sustain the central
     city's competitiveness in a region? Are transit cities more
     centrally oriented? Why?
     These questions can be addressed in research undertakings. 
The following is a brief guide to some of them:


Net Change
     Does transit contribute to metropolitan comparative advantage?
A key question is whether the presence of extensive transit ser-
vices provides a significant advantage among cities to attract
business or other development.  The BART study is the only study to
expressly address this question.  The BART study found that the
system did not change the economic trends of the region.  No
intercity comparative study has been conducted .
     One aspect of the intercity competitive factor is the
contribution transit makes to the ambient accessibility in the
metropolitan region.  Only immense changes cause significant land
use effects in today's cities; the effects of accessibility are
often a scale effect.  Examples of a scale effect are transit
investment in New York at the turn of the century when little
accessibility preceded it or in western cities with the advent of
freeway. (The BART system was only an increment to an already
extensive transit system in the Bay Area).  On the other hand,
transit investment, as in Atlanta, may prove attractive as a signal
of a civic interest and as a response to prospective congestion
concerns.
     Can transit contribute to turning around a low growth or
declining area? Of particular focus here are some of the cities
that sought to turn around a negative development situation through
transit investment.  Whereas Washington, D.C, San Francisco, and
Atlanta were high growth areas needing transit to respond to prob-
lems of capacity, other areas have sought to turn around economic
problems by the stimulative effects of transit development.  Aside

74   Appendix





from the obvious short-term effects of the infusion of large
quantities of state and federal dollars, did transit investment
help attract new growth or help reverse decline? This is of
particular interest in Buffalo where transit investment was a key
element in an economic development strategy and to a lesser extent
in Portland and Detroit.


Redistributive Effects
     Beyond the net change effects on metropolitan area growth
potential are the questions of redistributing land development As
noted, this can be as crucial as the intercity competitive effects. 
Two elements to the redistribution question are:
1.   Traditional research questions about transit development
     impacts around stations or along transit corridors; and
2.   Broader questions of the power of transit's ability to sustain
     the influence of the center city in a large metropolitan
     region where economic forces are acting centrifugally.
     Why is the influence of transit around stations so variable?
There is a significant body of research literature studying new
transit stations with and without growth effects - examples exist
of both.  Research may be able to clarify why these effects occur
in some instances and not in others.  Questions also exist about
the interaction of transit investment with other factors of
development such as special zoning treatment which may have
influence independent of transit access.  A pertinent area of
investigation is to establish the actual causative linkages
involved at stations rather  the general statistical, evidence;
i.e., in a high growth area around a transit station, to what
extent was transit a factor in location choices; to what extent are
residents, commuters, and shoppers actually oriented to the transit
system?
     Can transit aid the center city in its competition with the
suburban development trend? Transit investment's future role to
sustain the center influence of a metropolitan region is a factor
that will impact transit investment.  Effectively, all major
transit investments orient the access opportunities they provide to
the center.  If they are effective formers of land use, their
greatest effects should be felt in the attraction power they
generate for the center.  That influence can be tested.  It must be
recognized that the effect of transit access, however effective or
ineffective, is acting in a way countervailing other very powerful
forces that are tending to reduce the influence of the center. 
Further, the test of central influence should not be measured in
the effects on job locations only.  The power of the center for
entertainment, recreation, and education must also be considered.

                                                      Appendix   75





References

1.   Donald L. Emerson.  A Framework For Analyzing the Land Use and
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2.   Michael D. Meyer. Economic Development Impacts of Rail
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3.   Robert Cervero. light Rail Transit and Urban Development.  APA
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5.   J. T. Black, et al.  Downtown Office Growth and the Role of
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9.   E. Davis, 1. Brown and R. Holmes.  Transit-Linked Development
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10.  J. A. Page. et al. Catalog of Transit Station Impact Case
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11.  The O'Hare Transit Extension Before and After Analysis. 
     Chicago Area Transportation Study, 1986.
12.  Samuel L. Zimmermann.  "UMTA and Major Investments: Evaluation
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13.  Light Rail Transit: New Successes at Affordable Prices. 
     Transportation Research Board Special Report 221, Washington,
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14.  G. B. Arrington, Jr.  Light Rail and Land Use.  Tri-County
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15.  S. M. Edner and G. B. Arrington.  Urban Decision Making for
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16.  San Diego Trolley: The First Three Years.  SANDAG, UMTA,
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17.  T. J. McGean. et al.  Assessment of the San Diego Light Rail
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18.  R. E. Paaswell and J. Berechman. et al.  An Analysis of Rapid
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19.  The Impacts of UMTA Programs - Case Studies of Four Urban
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20.  M.D.Meyer. Discussion Paper on Identifying the Effectiveness
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21.  M. D. Irwin.  The Declining Significance of Space.  Department
     of Sociology Louisiana State University.  Presented at NCIW
     Conference on Research Needs for Transportation Investment and
     Economic Productivity, New Orleans, 1990.
22.  M. D.  and J. D. Kasarda.  Air Passenger Linkages and the
     Transmission of employment Growth Among Metropolitan Areas. 
     Publication Forthcoming& April 1990.
23.  The Economic Benefits of air Transportation.  Air Transport
     Association of America, Washington, D.C., 1988.

76   Appendix





24.  The Economic Impact of Civil Aviation on the U.S. Economy. 
     Partnership for Improved Air Travel, Washington, D.C., June 1989.
25.  J. P. Schwieterman and F. A. Spencer.  Alternatives to the
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26.  J. P. Schwieterman.  Airline Routes and Metropolitan Areas:
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     Transportation Research Record 1161, TRB, Washington, D.C., 1988.
27.  The Changing Government Roles in Airports.  Transportation
     Research Circular Number 316, TRB, Washington, D.C., 1987.
28.  The Economic Benefits of air Transportation.  Air Transport
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29.  D. S. McLeod.  Recommended Regional Economic Impact Procedures
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30.  F.P. Kulka. The Impact of the Genesee County Airport on
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32.  Current Literature on Highway Investment and Economic
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33.  The Land Use and Urban Development Impacts of Beltways. U.S.
     DOT, October 1980.
34.  Social and Economic Effects of Highways.  FHWA, 1976.
35.  Economic and Social Effects of Highways.  FHWA, 1972.
36.  Highways and Economic and Social Changes.  BPR, 1968.
37.  A. E. Pisarski.  The Nation's Public Works - Highways, Streets
     and Bridges.  National Council on Public Works Improvement,
     Washington, D.C., May 1987.
38.  A Study of the Social Economic and Environmental Impact of
     Highway Transportation Facilities.  State University, BPR, 1968.
39.  Richmond Beltway Impact Study.  Urban Institute, FHWA, 1978.
40.  Chicago/Kansas City Tollway Feasibility Study.  Illinois and
     Missouri DOTS, March 1990.
41.  Southwest Indiana Feasibility Study.  Indiana DCYI, February 1990.
42.  Highway 29145 Corridor Study.  Wisconsin DOT, March 1989.
43.  A. L. Politano and C. J. Roadifer.  Regional Economic Impact
     Model for Highway Systems (REIMHS).  Transportation Research
     Record 129, TRB, Washington, D.C., 1989.
44.  Business Location Decisions.  Pacific Consultants, U.S. DOT,
     November 1980.
45.  Transportation and Urban Economic Development.  National
     Council for Urban Economic Development, U.S. DOT, June 1982.
46.  A Survey of Techniques Used to Access the Influence of
     Transportation on Economic Growth Special TRB Panel,
     Transportation Research Board.  Washington, D.C., April 1982.
47.  Alan E. Pisarski.  Metropolitan and Intercity Transportation
     Investment and Economic Development.  Presented at NCHRP
     Conference on Research Needs for Transportation Investment and
     Economic Productivity, New Orleans, 1990.
48.  Scott L. Bottles.  Los Angeles and the Automobile.  University
     of California Press, Berkeley, 1989.
49.  "The Wheel Extended, " Mobility and the Shape of the New
     Tokyo.  Toyota Quarterly.  Tokyo, 1989.
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     States.  Third edition, U.S. Department of Transportation, 1988.

                                                      Appendix   77





51.  Michael Bell.  Institute for Policy Studies, The Johns Hopkins
     University.  Bottlenecks and Flexibility.  Key Concepts for
     Identifying Economic Development Impacts of Transportation
     Services.  Presented at TRB Williamsburg Conference on
     Transportation and Economic Development, 1989.
52.  Ronald E. Grierson.  Urban Economics - Readings and Analysis. 
     Little, Brown and Company, Boston, 1973.
53.  James Heilbrun.  Urban Economics and Public Policy.  St.
     Martin's Press, New York, 1974.
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     Publishing Company, Cambridge, 1976.
55.  John Meyer, et al.  The Urban Transportation Problem.  Harvard
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     Foresman and Company, Glenview, Illinois, 1980.

78   Appendix





The Effects of Added Transportation Capacity on Travel: A Review of
Theoretical and Empirical Results

Ryuichi Kitamura
Institute of Transportation Studies
University of California, Davis

Introduction
     The addition of transportation capacity affects potentially
all attributes of trips made by urban residents; i.e., time of day,
destination, mode, route, and linking of trips.  The impact could
be more pronounced if unsatisfied or latent demand exists due to
congestion (Cambridge Systematics, Inc., and JHK & Associates,
1979).  In the long-run, added capacity may influence a household's
automobile ownership decision, residence, and job location choice. 
Firms' location decisions will also be affected. Sooner or later,
waves of development start filling the fringe area. It appears
most certain that as long as the urban area continues to grow,
fringe land with good transportation access will be converted to
residential and commercial use.  The addition of transportation
capacity is one of the key contributors to urban growth.1
     Perhaps the most fundamental impact of added capacity is
attributable to urban growth stemming from the ability of
transportation capacity to support a larger urban population and
more extensive non-residential activities.  Obviously, this growth
has immediate impact on travel demand; an X percent increase in an
area's work force would probably lead to an increase in work trips
generation by approximately X percent.  Possible increases due to
changes in departure times, destinations, modes, routes, or even
induced trips, appear minute when compared with this primary growth
effect.
     However, if growth were controlled by strict land-use measures
or if growth in an urban area were supported by its political
constituencies, then the secondary impacts of added capacity would
no longer be a trivial issue.  One would need to address the
question: What is the trip-inducing effect of added capacity? If
highways were not congested, would people go out more often and
drive farther? One may also be concerned with the long-term effects
of added capacity upon the evolution of an urban area.  Would
people own fewer automobiles and use public transit more if the
capacity of the transit system increased? Would radial expansion of
the highway system merely contribute to ever increasing trip
lengths?
     Neither primary growth effects nor the secondary trip effects
of added capacity are thoroughly understood.  The growth effects
are not incorporated into the standard urban passenger travel
demand forecasting procedure in the sense that future land use is
predetermined, essentially independent of the future travel demand
and supply.  Nor are the effects of improved accessibility on trip
generation, trip chaining, and trip timing represented in the
procedure.  This is partly due to lack of theory.  Economic theory
is often too simplistic to account for the complexity of travel
behavior with the multitude of potential behavioral adjustments
(e.g., one can change any, or combinations, of trip frequency,
destinations, modes, routes, trip timing, and linkages).2 Attempts
have been made to construct travel behavior models that draw on
broader theoretical bases (e.g., Bhat, 1991; Koppelman and
Townsend, 1987; Pas and Harvey, 1991).  Yet many steps need to be
taken before these efforts can be reflected in the practice of
travel demand forecasting.

                                                      Appendix   79





     Furthermore, determining the effect of added capacity is not
at all a trivial task because it is concerned with intricately and
dynamically interrelated system components: transportation supply
system, land use, accessibility, and travel demand.  Transportation
supply system affects land use, as evidenced by land use devel-
opment, that seems to inevitably follow the construction of new
facilities.  Together, transportation supply system and land use
define accessibility.  Induced trips represent the effect of
accessibility on trip generation.  Travel demand, in turn, affects
the transportation supply system through the planning process. 
These interrelationships, with built-in lag time, imply an urban
system which may be viewed as a labyrinthine "ecological system."
Consequently, an attempt to model one variable (i.e., travel
demand) as a function of the rest encounters highly multi-collinear
explanatory variables, making the identification of each
contributing factor's effect impractical.
     This paper presents a review of theoretical and empirical
results in the literature that shed light to the effect of added
transportation capacity.  The purpose of the effort is to establish
a base from which future research effort can depart.  The review of
theoretical studies is limited only to those aspects of daily
travel behavior for which empirical observations are available. 
Studies on network assignment and departure time choice are outside
the scope of this study.  Theories and empirical evidence on long-
term impacts of added capacity are also outside the scope except
for a review of disaggregate choice models on household auto own-
ership.
     This paper is organized as follows: In the next section
several theoretical models and paradigms of urban travel behavior
are discussed; The following section offers a review of empirical
studies that examine the impact of highways on travel; The next
section addresses the limitations of the current demand forecasting
procedure, and the last section presents conclusions and future
research directions.


Theoretical Approach
     A comprehensive theory of urban travel behavior is difficult
to establish, perhaps because travel is such a fundamental element
of life.  Individuals travel for economic, social, psychological,
and physiological reasons.  Although some aspects of travel
behavior (e.g., travel mode choice) may be well described using
theories scattered in these academic disciplines, constructing an
embracing theory of urban travel and formulating a system of quan-
titative models has not yet been accomplished.
     Examining the impact of added capacity would require a more
fundamental understanding of why people travel.  It would also
require the accumulation of empirical evidence based on exact
measurement of each factor's effect.  As a precursor of such an
endeavor, the discussions in this section focus on microeconomic
formulations of travel behavior, the paradigm of cons in travel
time budgets, evidence offered by what may be called the
"ecological approach, " the effect of accessibility as a general
measure of the generalized cost of travel, and some of the
difficulties associated with identifying the effect of generalized
travel cost on travel (which is a function of the capacity the
supply system offers, the spatial distribution of opportunities,
and travel demand).


Economic Theory
     The cost of transporting goods and passengers plays a critical
role in theories of land use and urban development.  Theoretical
models have been constructed to explain a firm's decision locating
its plant, a household's choice of where to reside, or a retailer's
selection of store locations.  For example, a household may be
willing to live farther away from the city center and spend more
time commuting if that will allow more residential space to be con-
sumed.  The rent per unit space then, must decrease as the distance
from the city center increases.  Empirical observations often agree
with such relations theoretically derived for highly hypothetical
and abstract models of ur-

80   Appendix





ban areas (for a recent review see Berechman and Small, 1988).
     A very fundamental relationship in economics is between supply
and demand; the demand for a good increases as its price decreases,
while supply increases as the price increases; and an equilibrium
will be attained where the demand equals the supply, with the good
at an equilibrium price.  This can be applied to urban travel by
viewing transportation as a consumed commodity (e.g., Wohl, 1962). 
For illustrative simplicity, let the time cost-of travel be the
only cost, and let this cost be proportional to the inverse of the
average travel speed in a hypothetical urban area.  Then the demand
for travel increases as travel speed increases and travel cost
decreases.  But as demand increases (therefore, as traffic volume
increases), speed declines and travel cost increases.  The former
relation constitutes a demand curve and the latter a supply curve. 
The intersection of these two curves indicates an equilibrium
volume and speed.  An improvement to the roadway infrastructure
(increased capacity) would lower the supply curve (a larger volume
can be carried at the same speed) and the equilibrium point would
shift to the right to a larger equilibrium volume, a higher speed,
and a lower cost The message is quite clear: Added capacity will
lead to an increase in travel with the volume added after the
improvement representing "travelers diverted from other facilities,
those making more frequent trips, those switching from other modes
of travel, or those making entirely new trips" (op. cit., pp. 52-
53).  This, however, represents a highly simplistic and aggregate
approach to travel behavior.  People make trips to engage in
activities at different locations; the demand for travel is a
derived demand and should be treated as such.
     In their microeconomic derivation of a gravity model of trip
distribution, Niedercom and Bechdolt (1969) depict trip making as a
resource allocation behavior.  A visit by a trip maker situated at
i to a destination zone j, is assumed to produce a positive amount
of utility, with repeated Tij visits collectively yielding


Click HERE for graphic.

                                                      Appendix   81





from i to j. In this formulation, the net benefit to a household
derived from travel is maximized Beckmann and Golob also adopt
depictions of trip making as a resource allocation behavior and
briefly discuss the case where both monetary and time budget
constraints exist.3 The conclusion of their analysis is similar to
those discussed above: Trip frequencies will increase as the
generalized cost of travel decreases.4


Travel Time Budgets
     When trip making is viewed as a resource allocation behavior,
then the total travel resource that can be allocated becomes a
primal driving factor.  Zahavi proposes an alternative travel
demand forecasting procedure which explicitly incorporates time and
monetary budgets for travel.  Zahavi's paradigm of constant travel
time budgets and empirical observations on which it is based
(Zahavi and Talvitie, 1980 and Zahavi and Ryan, 1980) have led to
extensive debates (e.g., Downes and Emmerson, 1983; Supemak,
1982, 1984; Zahavi, 1982; Van der Hoom, et al., 1983).  Zahavi's
approach is one of a few principles of travel behavior that have
been developed into operational forecasting systems.  Its use has
been alluded to recently by Stopher (Applied Management and
Planning Group, 1990) as a possible approach to accounting for the
travel impact of added capacities.  A close review of the approach
appears to be warranted.
     The Unified Mechanism of Travel (UMOT) model is proposed as an
alternative to traditional approaches to urban passenger travel and
demand-supply relationships (see Zahavi and McLynn, 1983).  The
backbone of the UMOT model is the hypothesis of the constancy in
household travel budgets.  "The UMOT model maximizes the daily
spatial and economic opportunities per household, represented by
the daily travel distance, under explicit constraints.  The
constraints are the daily travel time and money expenditures per
traveler and per household, respectively.  These travel budgets
have been found to display consistent regularities and to be
transferable both spatially and over time" (op. cit., p. 137). 
This formulation of trip making as a travel distance maximization
process is based on the viewpoint that travel itself produces
utility; therefore, savings in travel time and costs will be used
for more travel.  It is, however, noted without further
clarification that "both the travel time and money budgets are
state variables that change during each iteration" (op. cit., p.
138).
     These assumptions underlying UMOT yield many interesting
insights, e.g., households respond to an increase in auto monetary
travel cost, not by reducing the level of auto ownership but by
choosing to hold automobiles of lesser quality, or of lower "car
factor" values.  The car factor represents the quality of the
vehicles that tend to be owned by households in each income group,
or "the type of car associated with each income group, namely above
or below a standard car, where the value of 1 ... signifies a
standard car" (op. cit., p. 144).
     At the same time, these assumptions seem to produce counter-
intuitive indications.  For example, Zahavi and McLynn report that
higher income households are able to satisfy their travel needs by
increasing vehicle ownership levels, but "low-income households, on
the other hand, cannot satisfy the demand for car travel to all
their travelers.  Furthermore, since the increasing number of
travelers have to be satisfied by other modes than car, say buses,
all which require travel expenditures, car ownership levels
actually decrease with increasing household size" (op. cit., p.
145).  Or, "gasoline consumption may increase, not necessarily
decrease, at some point along the increases in car unit costs ...."
The reason for this somewhat unexpected result is that decreases in
the car factor (namely, increasing the average age of cars) result
in increases in gasoline consumption" (op. cit., p. 149).  Perhaps
the most paradoxical is the result, "a reduction of bus fares ...
may allow low income travelers the transfer of the freed bus fares
to car travel ... conventional wisdom tells us that bus fare
reductions should attract car travel to bus travel, while the UMOT
model predicts otherwise" (op. cit., p. 151).  In other

82   Appendix





words, when bus fares are reduced low-income travelers can use the
resulting savings for auto travel.  While Zahavi and McLynn
maintain that this is an example of the Giffen effect with bus
trips being an "inferior good, " no empirical evidence is offered
in support of the result.
     It is not difficult to imagine that the UMOT model system is
at best controversial.  Downes and Emmerson (1983) note that "the
effects of trip characteristics on trip rates are not fully
understood" and present a study that examines the effect of
improved travel speeds on the trip length and frequency.  They use
1976 large scale household interview survey results from 12
municipalities of varying populations and sizes.  The study
separately analyzes a sub sample of 32,000 individuals who "only
traveled internally" within study areas (op. cit., p.174) and
concludes that the total travel expenditure decreases as travel
speed increases for those internal travelers, while it increases
with speed if external travel is included.
     The results thus cast doubt on the assumption of constant
travel time expenditure.  The study, however, does not explicitly
state how the average speed was defined for each traveler.  If the
average speed is defined as the total distance traveled by a
traveler divided by the total time it took (which is suggested by
the discussion on p. 176), then this variable is endogenous and the
results by Downes and Emmerson could be seriously biased.
     Van der Hoorn, et al., (1983) acknowledge that the UMOT
approach is "very appealing to policy makers and researchers
because it is conceptually simple and robust, the data requirements
are low and the model is easy to compute on a micro computer" (op.
cit., p. 156).  However, their effort to implement the model for
the Netherlands has led to the identification of several
limitations in the model, questionable mode use elasticities with
respect to their costs, and a finding that the auto ownership
component is "too simplistic" (op. cit., p. 168).  In his comments
to Vander Hoorn, et al, Zahavi notes that most of the limitations
are accounted for in the latest version of the UMOT model.
     Supemak (1982) points out the inconsistency that exists among
various measures of travel budgets (or, expenditures) and cites em-
pirical observations that contradict the hypothesis of constant
travel budgets.  In particular, Supemak reports that trip rates are
"more regular and stable"  travel time budgets, supporting the
conventional sequential approach that starts with trip generation
analysis.
     It is indeed unfortunate that Zahavi passed away before he was
able to complete the UMOT Model.  It is yet to be determined
whether the above counter-intuitive indications from the UMOT model
are logical consequences of the assumption of constant travel
budgets or mere aberrations resulting from a forecasting system yet
to be completed.


Accessibility and Added Capacity
An accessibility measure, representing the relative ease of
reaching opportunities in an urban area from a specific area within
it, may be interpreted as a general indicator of the cost of
travel.  Then, applying the economic principle discussed earlier,
residents in a high-accessibility area should tend to travel more,
not necessarily in terms of travel time or cost, but in terms of
trip rates or VMT.  Theoretically it is expected that trip
generation is positively correlated with accessibility.
     Added transportation capacity, whether by means of additional
freeway lanes, HOV lanes, or public transit lines, implies
increased accessibility in impacted areas.  The effect of added
capacity, then, can be examined by testing the relationship between
accessibility and travel, in particular, trip rates.  Note that
trip generation analysis, as practiced now typically does not
incorporate accessibility measures.  Trip production and attraction
are assumed to be functions of sociodemographic and land-use
variables but not accessibility.  Added capacity is not viewed as a
factor that causes changes in trip generation.5
     Since accessibility measures will vary wi an urban area,
cross-sectional data suffice in the test, longitudinal data,
although more

                                                      Appendix   83





desirable, may not be necessary.  This approach is more attractive
than the comparison of changes in travel patterns before and after
a capacity improvement.  The main advantage is the availability of
needed data in practically every metropolitan area.  There is no
need to wait for a capital project in order to obtain before-and-
after observations or to establish a control group in order to
capture time effects.
     Attempts to establish positive links between accessibility and
trip generation, however, have not been successful.  The most fre-
quently referenced study is by Nakkash and Grecco (1972).  Their
results exhibit statistically significant effects of accessibility
only on school trip production and attraction; accessibility
measures are not significant in most trip generation equations. 
Taken literally, the results lend support to the current practice
of trip generation analysis by showing the absence of capacity
effects on trip rates with the only exception being school trips. 
Before drawing any conclusion, however, it is necessary to review
the relationship among the key contributing factors of urban trip
making.


Ecological Correlations
     Urbanization is a result of the benefit of clustering: "To
achieve most of the goals that human beings have, "cluster" is more
efficient than "scatter" (Smith, 1975, p. 26).  Although the
preference for isolation may exist, it may be preferable to
surrender "isolation or control over space in the interest of
conserving transportation resources" (op cit., p.27).  This is
especially the case for production due to both internal and
external economies of scale.  Transportation cost, then, explains
the intensity of land use, population density, and rent (land
value) that decline with the distance from the urban center. 
Because the city center represents a concentration of
opportunities, accessibility in general decreases with the distance
from the city center.
     The observation that certain levels of residential density is
needed for public transit to be viable (Pushkarev and Zupan, 1976)
implies that public transit either offers limited service or is not
available at all in low density areas.  Residents in these areas
are then required to have automobiles to gain mobility- This is
well supported by empirical observation (e.g., Mogridge, 1986). 
For data from Portland, OR, and Vancouver, B.C., Shindler and
Ferreri(1967) derive bivariate correlation coefficients among the
logarithm of net residential density, transit to-auto accessibility
ratio, and the number of automobiles per dwelling unit as shown in
the table below.

                                a.           b.        c.

a.   Net Residential Density
     (logarithm)              1.000          0.703     -0.691

b.   Accessibility Ratio
     (transit to auto)                       1.000     -0.652

c.   Number of Autos per
     Dwelling Unit                                     1.000

     Source:   Shindler and Ferreri (1967)


     It is also well established that auto ownership is most
significantly associated with transit use.  Shindler and Ferreri
(1967) summarized that the relationship between auto ownership and
transit use "was so strong, that auto ownership dominated all other
factors in explaining the trip-making split between auto and
transit travel.  Thus, for any given level of auto ownership in an
area, transit use was, in a sense, predetermined regardless of the
quality of service" (op. cit, p. 24).  Additional variables that
may enter the picture here are household size and income.  These
variables are correlated positively with auto ownership and
negatively with residential density and accessibility ratio.  This
may be explained in part by the tendency that households with
children prefer single family housings and suburban lifestyles. 
Thus, an urban area exhibits intricate correlations among variables
that are closely related to household travel behavior.  These
correlations, which

84   Appendix





may be called "ecological correlations, " are results of decisions
made by households and firms and actions taken by public agencies
over time.6


Effects of Added Capacity
     A direct consequence of such strong and clear relationships
among residential density, household size, income, and auto
ownership, is the multi-collinearity that exists among these
variables that have traditionally been considered to most strongly
influence household trip generation.  Being defined as a function
of land use and interzonal travel time variables, accessibility
measures are also multi-collinear with the other contributing
factors.  As a result, it is extremely difficult to determine the
independent effect of each contributing factor.7
     Consequently, it has not been possible to produce definitive
answers to such seemingly rudimentary questions as: "Does an
increase in capacity induce trips?" or "Can we decrease automobile
ownership and increase transit use by increasing residential
density?"
     The problem is further compounded due to the endogeneity of
these "explanatory" variables.  Although variables representing
land use, auto ownership, and accessibility have traditionally been
treated as exogenous variables that are determined outside the
system, they actually not only feed into each other but also are
influenced by travel demand over time.  Residential and commercial
land use and transportation networks together define accessibility
and travel demand.  Travel demand and transportation supply
characteristics determine the levels of service available on
networks.  Levels of service, in turn, lead to the enhancement of
network characteristics through planning actions, which lead to
further residential and commercial land-use development.  As this
cycle repeats itself over time, it creates an evolving system in
which all pertinent variables are endogenously determined within
the system.  The effect of capacity increase has not been examined
in this dynamic context.8
     Summarizing the discussion of this section, economic
formulations of trip making offer unambiguous indications that
added capacity, which implies decreased cost of travel would lead
to more trips and VMT.  Furthermore, they have shown that travel
time, or monetary budgets, play important roles.  Travel budgets,
or travel expenditures to be more precise, are clearly determined
by households; although no models reviewed here attempt to model
the process of determining a travel budget endogenously.  The most
desirable level of travel expenditure of either time or money will
vary from household to household or from situation to situation. 
The notion of forecasting future travel demand based on the
assumption that the travel expenditure of a household remains
constant over time is not well founded and appears to produce
results that cannot be theoretically supported.  Then how does a
travel expenditure, or trip making in general, change in response
to changes in capacity and resulting changes in generalized travel
costs? No definite answer to this question appears to be available. 
The discussion here pointed out the multi-collinearity among the
factors that contribute to trip making, which is a consequence of
ecological correlation that prevails in an urban area.  In the
sections that follow, pieces of empirical evidence are put together
to form empirical conclusions on the impact of added capacity.


Impacts of New Highways
     The literature on the impacts of new highways appears to be
dominated by cost-benefit analyses of highway investment.  For
example, a sample of articles in Transportation Research Record
includes economic impact analyses by Batchelor et al. (1975),
Gaegler et al. (1979), and Mahady and Tsitros (1981); articles
emphasizing property values as a major element in the cost-benefit
analysis by Gamble et al. (1974) and Langley (1976); and articles
focusing on community values by Ellis (1968) and Falk (1968). 
Empirical studies of the impact of new roadways on travel behavior,
however, are surprisingly few and far between.9

                                                      Appendix   85





     A report by U.S. Department of Transportation (1981)
concludes:
     It seems clear from the studies which have been conducted over
     many years that highway service level improvements do induce
     increases in VMT.  However, the magnitude of induced traffic
     is thought by some to be quite small and, by others, to be
     significant in certain circumstances (op. cit., p. 22).
On the other hand, Smith and Schoener (1978) maintain:
     A frequent statement advanced by transportation professionals
     is that highway improvements, by inducing travel, create more
     congestion  they eliminate.  Although few data exist to
     support this statement, it has gained legitimacy by sheer
     repetition.
This view is repeated in a Research Results Digest issue
(Transportation Research Board, 1980).
     In this section, available evidence is reviewed to assess the
effect of new highways on travel, especially on induced trips.


Taxonomies
     Many highways have been built during the periods when urban
areas underwent demographic and economic growth.  Urban growth has
been accompanied by new highways, and new highways were sooner or
later surrounded by growing suburbs.  In this sense, new highways
have been synonymous with urban growth and growing travel demand. 
The first step in the effort to reveal structural relationships
between added capacity and travel demand would be to define
different elements of the traffic that seemingly fills up a new
highway almost immediately.
     Zimmermann et al. (1974) propose that traffic on a (new or
capacity-improved) highway be classified into:
-    existing traffic, 
-    development traffic (due to land-use changes), 
-    natural growth (demographic and socioeconomic changes), 
-    diverted (from other streets or highways), 
-    induced (new trips made because of the new highway), 
-    transferred (from other modes), and shifted (to new
     destinations).
The last four categories are consequences of a new highway of which
induced traffic is a part.  Holder and Stover (1972) propose to
distinguish between "apparent induced traffic" and "true induced
traffic" (read in CSI and JHK, 1979, p. E-1).  Similar to Zimmer,
et al., Holder and Stover also attribute changes in traffic counts
due to "cultural traffic" (due to shifts in demographic or
socioeconomic characteristics), converted traffic (from other
modes), developed traffic (resulting from land-use change), and
diverted traffic (from other streets and highways)" (op. cit. p. E-1).
The development traffic and natural growth traffic as defined
by Zimme et al., represent increases in trip generation that are
accounted for in the land use model that provides input to the trip
generation models in the sequential demand forecasting procedure. 
Similarly, diverted traffic, transferred traffic, and shifted
traffic are, in principle, accounted for by the trip distribution,
modal split, and network assignment phases of the procedure
(although actual practice may be less than ideal (see Harvey
[1991], Applied Management and Planning Group [19901).  This leaves
induced traffic unaccounted for in the sequential demand
forecasting procedure.  Also unaccounted for is the effect of a new
highway on the temporal distribution of traffic, which is not
considered in these classification schemes of traffic.
     The review of empirical evidence in the literature presented
below indicates that new highways do have impact on VMT, presumably
due to a large extent to shifted traffic.  This impact is well
represented by the demand forecasting procedure.  The impact of a
new facility on induced traffic, however, is not evident.

86   Appendix





Impact on VMT
     The average trip length appears to increase with the
construction of new highways.  Voorhees, Bames, and Coleman (1962)
cite that the average work trip length in Baltimore increased from
2.6 miles in 1926 to 4 miles in 1946, and to over 5 miles as of the
writing of the paper.
     Bellomo et al. (1970) also notes similar historical increases
in trip lengths.  For example, "In Detroit the mean auto driver
work trip length in miles increased by 18 percent as the area
increased in population by 14 percent, and the average speed of
network increased by 12 percent between 1953 and 1965" (op. cit.,
p. 1). Presumably this is due to a large extent to the geographical
and demographic expansion of the area, leading to substantial
development and natural growth traffic and, probably to a lesser
extent, to shifted traffic.
     Voorhees, et al. (1966) offers quantitative indications of the
effect of population and network speed on trip length.  Based on
aggregate data (average trip duration, etc.) from 23 cities, the
following model was developed:


     L = 0.003P0.20S11.49


Where:
     L = the average trip length in miles.
     P = the urban area population.
     S = the average network speed in mph (op. cit., p. 31).

The positive effect of network speed on trip length is evident. 
The effects of the "physical structure of an urban area" on the
trip duration and distance are also noted in the study.  The
distribution of opportunities is not considered in the study.
     Accounting for the size and physical structure of an urban
area, the network speed, and socioeconomic factors are considered
crucial in forecasting future trip length (op. cit., p. 36).  Based
largely on simulation results, the effects of network speed are
summarized as:
     (a) change in the average trip length (miles) for uniform
     density cities will probably be directly proportional to the
     square root of changes in network speed; and (b) change in the
     average trip length (minutes) will probably be inversely
     proportional to the square root of changes in network speed-
     experience, however, has shown that peak hour speeds have not
     greatly changed in large metropolitan areas (op. cit., p. 36).
Then, an addition of capacity, which would lead to a higher highway
speed, would also lead to an increase in VMT.
     The results reported by Frye (1963) also indicate that a
capacity increase has a direct impact on traffic beyond development
and natural growth traffic.  The opening of the Congress Expressway
in a 16 square-mile area in the western suburbs of Chicago led to
an increase in the total VMT in the area by 21 percent between 1959
(before opening) and 1961.  An increase of 7 percent could be
expected in the area due to natural growth.  Frye's findings are
summarized in U.S.DOT (1981, pp. 20-21) as: "About half the total
increase (10.5 percent) was due to diversion of traffic from areas
outside the study area.  The other 3.5 percent is attributed to
induced traffic (i.e., new or longer trips) and adverse travel (the
extra VMT generated by travelers going out of their way to use the
new facility)...."10


Induced Trips
     Unlike the other types of traffic on a new highway, induced
traffic must be captured in the trip generation phase of the
sequential forecasting procedure.  Trip generation models typically
use demographic and socioeconomic variables for residential trip
generation (e.g., household size and auto ownership) and land-use
variables (e.g., zonal employment, retail and floor area) for non-
residential trip generation.  It is not common practice to use
variables that represent transportation supply characteristics.  In
fact, the current practice of trip generation analysis appears to
be based on the premise that there exist constant household trip
rates that do not change over time, do not vary within or

                                                      Appendix   87





across metropolitan areas, and are unaffected by the levels of
service on transportation networks.  Typical examples can be found
in the Institute of Transportation Engineers (ITE) trip rates (UE,
1979), "quick response" demand forecasting procedures, and computer
program packages (e.g., Sosslau et al., 1978).  Contrary empirical
evidence does exist.  For example, Goulias et al. (1990), in their
analysis of 1980 Detroit home interview travel survey results, find
that dummy variables representing the county of residence are
significant in many of the household trip generation models by pur-
pose estimated in the study.  Yet no compelling indicator of trip-
inducing effect of added capacity appears to be offered in the
studies reviewed below.
     As noted earlier, Nakkash and Grecco (1972) present formal
statistical tests of the significance of accessibility measures in
trip generation equations.  They argue, "Conceptually, there is not
strong basis for assuming that tripmaking is independent of the
transportation system" (op. cit., p. 99).  The issue addressed here
is precisely that of induced trips in the narrow sense as defined
by Zimmermann et al., (1974).  If, as economic theory implies, a
decrease in the generalized cost of travel leads to an increase in
trip making, then households residing in zones with high
accessibility would exhibit higher trip rates.  Nakkash and Grecco
examine this hypothesis by testing the statistical significance of
accessibility measures in trip generation models.
     The method used is straight forward.  A "relative
accessibility measure" is defined by trip purpose using destination
"mass" terms and friction factors (based on auto travel times, op.
cit., p. 102) and normalizing it as follows:


Click HERE for graphic.


     This measure is introduced into trip production and attraction
models by purpose developed in the Indianapolis Regional Transpor-
tation and Development Study (altogether 13 models are defined). 
The models are estimated with and without stratification which
divided the study area into central and non-central areas (the
former comprises 105 zones out of the 395 zones in the study area,
op. cit., p. 103).  The results of this analysis are,
unfortunately, inconclusive.  Presumably due to the multi-
collinearity problem discussed earlier, Nakkash and Grecco report
that often "no satisfactory models were developed, " or "models
were developed but no statistical testing was possible" (op. cit,
p. 107).  Only two pairs of trip production models and two pairs of
trip attraction models are successfully estimated that can be
legitimately used to test the significance of the accessibility
measure.  Of these, only one production model and one attraction
model (both for home-based school trips) offer significant results.
(The results are quite counter-intuitive as school trips are of
mandatory nature and should be least influenced by accessibility. 
This may have been caused by the practice of excluding non-
motorized trips from trip diaries that were prevalent at the time
their data were collected.)
     It is entirely possible that trip generation is in fact
largely unaffected by accessibility, as suggested by the Nakkash
and Grecco study.  However, it is also possible that, as noted re-
peatedly in this paper, multi-collinearity among the explanatory
variables may have led to the insignificant accessibility
coefficients.  The models may have been subject to specification
errors; introducing the accessibility measure as a linear additive
term may not have been appro-

88   Appendix





priate.  Accessibility measures are another potential problem. 
These zonal variables tend exhibit small variations across zones
and erroneously represent the true accessibility available to each
household.  Finally, the aggrega zone-based analysis may have been
too insensitive to detect the effect of accessibility.
     Kannel and Heathington (1974) examine panel of households
interviewed in both 1 and 1971.  The same panel of households is u
in their 1973 study of the stability in trip generation analysis. 
The objective of this 1974 study is to examine the hypothesis that
"the trip production from households is affected by the ac-
cessibility of the household to major activity centers within the
urban area" (op. cit., p. 78).  The accessibility measures
developed by Nakkash (see Nakkash and Grecco, 1972) are used in the
study.
     Kannel and Heathington use causal models to examine cause-
effect relationships among several endogenous variables including
accessibility, auto ownership, and mobility.  The indicator of
mobility is the number of homebased (presumably motorized) trips. 
Two alternative model structures are examined (each structure is
applied to the 1964 and 1971 data and leads to very stable sets of
coefficients).  In the first structure, accessibility affects both
auto ownership and trip generation negatively.  In the second
model, which is preferred to the first by the authors, the direct
link from accessibility to trip generation is eliminated.  Thus,
accessibility affects mobility, but only indirectly, through
automobile ownership.
     Smith and Schoener (1978) examine the impact of 1-95 based on
"data from origin-destination travel surveys conducted by the Rhode
Island Department of Transportation in Providence for 1961 (before
construction of 1-95) and 1971 (after I-95)" (op. cit., p. 152). 
Households are cross-classified according to household size and
auto ownership.  The dependent variables are VMT per household,
vehicle hours of travel (VHT) per household, and auto driver trips
per household.  Repeated cross-sectional data are used to address
these issues.  The 1961 sample contains 11, 467 households, but the
1971 sample contains only 855.  The study concentrates on vehicular
trips; "all trips that were not auto driver trips" were eliminated
from the data set (op. cit, p. 154).  The study area is divided
into two areas: the portion inside the influence of the new highway
and the portion outside it.
     Smith and Schoener (1978) correctly point out that "Many
previous studies have shown that a correlation exists between
aggregate highway supply per capita and VKMT per capita.  The
existence of such a correlation, however, does not guarantee the
existence of a causal relationship between the two variables" (op.
cit, p. 153).  Their analysis based on household data accounts for
this problem and offers extremely interesting statistics.  They
conclude:
     The comparison of the resulting matrices revealed that the
     highway did not increase trips or VHT, but it did increase
     VICMT.  This allows the tentative conclusion that travelers
     increase their VKMT until they use up a given amount of travel
     time.  This conclusion supports the standard system-
     insensitive approach to trip generation as well as the use of
     travel time as an impedance in trip distribution (op. cit, p.
     152).
     The study, however, is subject to limitations.  First, the
sample size for the "after" period is extremely small, probably
producing the tendency of accepting null hypotheses of no change. 
Second, the method used to test the statistical significance of
change is less than ideal.  Instead of examining the number of
significant pairwise statistics in before and after cross-
classification tables, the analysis of variance should have been
used.
     The concurrent processes of the proliferation of automotive
transportation and the decline of urban public transit are well
documented by aggregate historical data.  The impacts of individual
highway projects on transit use are less frequently documented.  An
interesting exception is a study by Richards and Beimbom (1973)
which, based on longitudinal transit ridership records before and
after the

                                                      Appendix   89





opening of a highway route, indicates that transit ridership began
d g before the highway opening due to residential and commercial
relocation, and that opening itself had only limited impact on
ridership.
     The very question of induced traffic is addressed in NCBRP
Project 8-19 (CSI and JHK, 1979 and TRB, 1980).  The study is
admittedly inconclusive, reflecting the complex nature of trip
making, the presence of a wide range of contributing factors, and
the resulting difficulties associated with its investigation.  Sev-
eral observations are made in the study.  Whether person trips will
increase or not is said to depend on the characteristics of the
transportation system such as the reduction of off-peak travel
times and costs or the level of congestion before the system change
(op. cit., p. 2-5).  "The increase in person trips produced by a
supply increase may or may not result in an increase in the number
of vehicle miles traveled, depending upon the nature of the supply
change" (op. cit., p. 2-6).  VMT may decrease if the supply change
decreases the distance between prominent origins and destinations
or if it encourages multiple occupancy vehicles.
     Importantly, "A congested facility generally reflects the
presence of unsatisfied or latent demand for trip making that may
be satisfied if travel conditions are improved by the construction
of new transportation facilities" (op. cit., p. 2-5).  It is noted
that non-work trips are more sensitive to supply characteristics,
and "the supply change must affect the off-peak travel conditions
within the corridor" to have impact on the volume of person trips
(op. cit., p. 2-5).  These and the number of other observations
made in the report suggest difficulties involved in stating the
effect of added capacity in general terms.  Whether a capacity
addition leads to induced trips or not needs to be determined case
by case while considering all the supply characteristics and other
contributing factors.


Conclusions
     Assessing the impact of added capacity is a complex task
because of the intricate causal relationships among transportation
supply, land use, accessibility, and travel demand.  The resulting
simultaneity and endogeneity make the use of complex analytical
methods inevitable; it is unreasonable to expect that simplistic
analyses based on limited data bases will properly address the
issue.
     At the same time, changes in travel demand are difficult and
time consuming to measure precisely.  Although carefully designed
evaluation studies may offer valuable insights, the case-specific
nature of impacts as discussed in CSI and JHK (1979) suggest that
generalization of their results may be difficult.
     One conclusion to be drawn from this literature review is that
only limited utilization has been made of existing travel survey
results.  Only a few studies have used accessibility measures while
no studies have attempted to examine the interaction between land
use and travel.  It is quite likely that this is due to
unavailability of suitable data, despite the many origin/desti-
nation surveys.
     Traditional origin/destination surveys have been conducted in
practically every metropolitan area, quite often at up to three
time points that are approximately 10 years apart.  Usually
metropolitan planning organizations (MPOS) prepare network and land
use data that accompany origin-destination trip records.  These
data files, however, do not seem to be well archived, well
documented, or easily available for research purposes.  If complete
trip, network, and land-use data sets can be made available from
selected metropolitan areas of different sizes and densities, they
will form a powerful data base that will extend beyond the many
limitations discussed in this study.  The use of existing origin-
destination data appears to be a very cost-effective and an
expeditious approach in addressing the added capacity issue.  This
and other points are itemized in the following tentative summary of
this study:
-    There is no empirical indication that added capacity generates
     a significant volume of induced traffic.
-    The standard sequential procedure is ca-

90   Appendix





     pable of forecasting diverted, transferred, and shifted
     traffic.
-    Abbreviated application of the procedure, unwarranted attempts
     to transfer models, and extrapolation of the models to inap-
     plicable options are unfortunately present.
-    A better understanding of trip timing decision is necessary,
     especially for non-work trips.
-    A better understanding of trip chaining behavior is also
     needed.
-    Impacts on auto ownership, residential and job location
     choice, and land use need to be better understood and
     incorporated into the forecasting procedure.
-    Existing data can be better used with more elaborate
     statistical methods to test behavioral theories.
-    Existing data can be used in multi-regional and multi-period
     comparative analyses of trip timing decisions, trip chaining
     behavior, and the issue of suppressed trips.
-    Likewise, existing data can be used to examine the effect of
     congestion on mode and destination choice.  Improving the
     conventional forecasting procedure can be best achieved
     through analysis of cross sectional data, because dynamic
     models derived from longitudinal (especially panel) data may
     not be compatible with cross-sectional models.
-    More widespread use of panel surveys is encouraged.

                                                      Appendix   91





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Notes


     1This is not to say that transportation capacity alone can
induce growth in an urban area.  The extensive discussions on the
subject of transportation investment and urban growth found in the
literature (e.g., Bone and Wohl, 1959; Levitan, 1976) suggest that
transportation capacity is just one of the factors that jointly
contributes to growth and development (Deakin, 1991).
     2Perhaps most realistic cases are analyses of the shopping
trip frequency and destination choice (e.g., 
Narula et al., 1983; Thill, 1985).  But even they are extremely
simplistic.
     3This work is said to be the basis of Zahavi's UMOT model
system discussed next (Zahavi and McLynn, 1983).
     4These approaches do not consider the consolidation of several
visits to several destinations into one trip chain (e.g., a trip to
work and a trip to shop combined to form a chain of work trip,
shopping trip, and home trip), or consolidation of several visits
made to the same destination into me visit (e.g., one weekly
shopping trip instead of seven daily trips).  Another weakness is
that no attention is given to how a time or monetary budget for
travel is established.
     5A notable exception is MTCFCAST, a model system developed for
the Metropolitan Transportation Commission (MTC).  This model
system is discussed later in this paper.
     6However, note that ecological correlations are consequences;
they are not causes that will lead to changes in the future.
     7The approach frequently taken when multi-collinearity is
present is to eliminate some of the multi-collinear variables to
produce a set of relatively independent explanatory variables.  It
is not surprising if accessibility measures to be the first to be
eliminated because, unlike household size, car ownership, or
income, they are aggregate measures defined for traffic zones.  As
such, they are subject to measurement errors and exhibit smaller
variations (see, e.g., McCarthy, 1969; Fleet and Robertson, 1968)
and are likely to have less significant coefficients associated
with them.
     8The problem is even more complex when regional demographic
and economic growth is take into account.  This leads to another
issue of whether transportation capacity leads to regional growth. 
As noted earlier, the extensive discussions on this subject found
in the literature suggest that transportation capacity is just one
of the contributing factors.
     9A very recent, notable exception is a study of a new ring
road in Amsterdam, the Netherlands, to be presented at the
forthcoming 1992 TRB Annual Meeting.  Unfortunately written
documents are not available in time for " presentation.
     10The term, "induced traffic, " is used in a broader sense to
include both induced and shifted traffic as defined by Zimmermann
et al. (1974).

                                                      Appendix   95





96   Appendix





Effects of Added Transportation Capacity on Development

Michael V Dyett, AICP
Blayney, Dyett, Greenburg

Types of Effects on Development
     Added transportation capacity, both improvements to the
existing system and new facilities and services, may affect the
following aspects of urban development:
-    Location (distribution effects versus growth-inducing
     effects -net additions)
-    Type (residential versus commercial/industrial)
-    Density/intensity(new development versus redevelopment)
-    Timing of projects, lease-up and occupancy


How Development Effects Occur
     Land use effects traditionally are determined on the basis of
changes in accessibility, which in turn affect peak-hour trips,
particularly home-based work trips.
     Missing Link: Impact of added capacity on latent travel
demand, primarily related to discretionary, non-work trips, and the
resulting implications for land use and pressures for new
development and redevelopment (intensification of use).
     In urbanized areas, additional transportation capacity alone
may facilitate or promote development, while in urbanizing and new
growth areas, whole packages of facilities, including water, sewer
and drainage improvements, and schools, are needed.


Setting
Factors affecting the magnitude of development include:
-    Land use constraints (geographic, economic, and political)
-    Local and regional planning environment (high-regulating
     versus low-regulating communities)


Dimensions of New Capacity
-    Types of improvements (facility and service improvements for
     existing systems versus additions to the system - new highway
     and transit capacity)
-    Location (central city, older urban areas, urbanizing fringe,
     free-standing communities)


Strategies for Dealing with Development Impacts

     The key is effective, long-range, comprehensive, coordinated
land use and transportation planning supported by local political
leaders.  Transportation improvements as well as private
development projects consistent with such plans should not be
considered growth inducing and should not be subject to separate
impact analysis and mitigation beyond "fairshare" contributions to
citywide improvements and specific, off-site improvements not
contemplated by the local jurisdiction's comprehensive plan.
     When political leadership does not "buy into" such planning,
cal solutions rarely are feasible.  Moreover, new capacity is
likely to have greater growth-inducing effects, especially if other
public facilities and services are available to accommodate new
development.
     In making decisions on whether to add transportation capacity
and to approve major development projects, federal, state and local
officials should focus on how to resolve conflicts through multi-
jurisdictional planning, not

                                                      Appendix   97





how to solve transportation problems with management, engineering
or pricing proposals that they not have political consensus.  It
also makes sense to distinguish projects that are consistent with
comprehensive p and zoning from those requiring plan amendments and
rezoning.  The decision-making process should include the following
steps:
-    Design equitable proposals;
-    Facilitate constructive negotiation with the community and
     between affected jurisdictions;
-    Make decisions based on plans and packages of improvements,
     not individual improvement projects which are not correlated
     with land use plans; and
-    Compensate those adversely affected.


Approaches for Studying These impacts
     Two sets of research questions are posed; the first is related
to general issues of concern about development impacts, while the
second focus more specifically on questions related to the
development process and the role of added transportation capacity
in development decisions.

General Considerations
-    If adding capacity in a built area does not noticeably reduce
     congestion because of latent demand and induced development,
     why are we doing it? Is it just to increase mobility with
     related economic benefits? What about mobility for the
     disadvantaged areas?
-    What criteria should be used to evaluate the development
     impacts of transportation improvement projects in urban areas,
     recognizing the impossibility of congestion reduction in urban
     areas over the long term (safety, mobility, land use com-
     patibility, fit with local planning policies and community
     needs, air quality implications, desire to influence mode
     split)?
-    If level of service standards are correlated with land use,
     how should through-traffic be evaluated in judging local
     compliance with these standards? Should different standards be
     used for the urban core versus the urbanizing fringe of
     metropolitan areas?
-    Recognizing that congestion is needed to get people to change
     travel habits, does it make sense to use level of service
     standards for individual transportation and private
     development projects, or should they be reserved for system
     and corridor planning?
-    Under what conditions can new capacity be added without
     growth-inducing effects?
-    When will new capacity contribute to "economics of
     agglomeration" or, by contrast, foster more dispersed
     development?
-    How should such development stimuli be incorporated into
     travel demand modeling?
-    When is added capacity really "new" and, therefore, growth
     inducing? Many proposed projects have been on local and
     regional plans for years, so effects on new development are
     difficult to isolate.
-    Does it make sense to distinguish improvements oriented to new
     development, recognizing that trips per capita have been
     increasing and there is no baseline of unchanging demand? Is
     the potential for induced travel the same, and what are the
     resulting land use implications?


Specific Questions Related to Development Process
-    How do developers perceive access versus congestion? Although
     access is more important, does the potential for future
     congestion affect calculations of project value and internal
     rate of return, or is congestion considered a cost of doing
     business that is unlikely to affect project lease up rates?
-    Does a proposed congestion management program translate into
     different, higher capitalization rates for revenue-produc-

98   Appendix





     ing property? Can these in turn be used to calculate an
     ability to pay for off-site improvements?
-    When do strategies designed to promote jobs/housing be have an
     impact on trip lengths and other travel characteristics (trip
     generation, mode split, etc.)?
-    What is the duration of development effects attributable to
     added transportation capacity? Are they short-run in nature,
     resulting in "one-time" shifts which then diminish as
     congestion increases, or is the perceived improvement in
     mobility resulting in a larger commute shed or greater
     potential retail market of longer-term economic benefit?


Regional Implications:
Modeling Studies in the San Francisco Bay Area
-    Build versus no-build scenarios for Metropolitan
     Transportation Commission
-    Implications for land use


     Association of Bay Area Governments, Assessing the Future.  A
Sensitivity Analysis of highway and Road Improvements on Growth in
the San Francisco Bay Area, Oakland, April 1991 (Working Paper 91-4).

                                                      Appendix   99








Institutional, Financial, and Social Impacts of Induced
Transportation:
Speculations on the Need for Research

Sheldon M. Edner
Planning Support Branch
Federal Highway Administration

Focus
     Additional capacity in a corridor primarily affects the
distribution of presumed subsidiary benefits of transportation
improvements. While the primary beneficiary may be the transport
user, improvements are often justified in terms of their
contribution to development (economic and otherwise) or mitigation
of transportation related problems (e.g., congestion, air
pollution, mobility disadvantage, etc.). These issues are not
spatially limited to the corridor, but extend out reciprocally into
the broader community in terms of impacts and the acquisition of
resources to construct the added capacity.  Hence, corridor
improvements, both generically and specifically (in terms of adding
carrying capacity), tend to shift existing balances in terms of
institutional and community goals.  Further, they are susceptible
to significant environmental (economic, social, technological,
etc.) influences because their consequences and benefits are not
limited to or based solely on the user.


Key Issues
Changes in spatial accessibility: Who benefits, who loses?
-    Region
-    Community
-    Neighborhood
What is the impact on coalitions that controls decision making and
is affected by spatial distributions of benefits?

Who is impacted by plan and project time horizons?

Who controls the horizon?

How should the sub-regional benefit distribution of regional
projects be handled?

Flexible versus inflexible systems: adapting to changing
metropolitan contexts (intervention of political, economic,
technological, and social change)?


Institutional Questions
Impact of overlapping jurisdictional boundaries:
-    Integration of general and special purpose governments units
-    Role of quasi-government agencies
-    Dynamic versus fixed boundaries

Number, kind, and role of institutions:
-    Planning processes and decisions
-    Operating agency role
-    Linking plans and operations

Ripple effects:
-    ROW acquisitions and corridor preservation
-    Zoning
-    Long-term land-use plans
-    Utilization of ancillary systems
-    Feeder systems
-    Employer incentives
-    Design standards

Growth boundaries and management:
-    Urban versus rural
-    Urban, suburban, and exurban

                                                     Appendix   101





Financial Issues
-    Scarce resources
-    Time lags in resource commitments
-    Relative stake and share
-    Political trade-offs in time
-    Public versus private goals: costs of alternative financing


Time Horizon: Who and How Far Out Are Plans Made?
-    Inconsistent horizons for institutions


Changing the Local Decision Calculus
-    What makes a coalition?
-    Written and unwritten rules
-    Exchange, dependency


Intervening Issues: Differential Consequences of Commitments
-    Convention centers
-    Jails
-    Air quality
-    Energy
-    Housing


Information and Decisionmaking: Who Knows What Is Going On?.
-    Building permits, zoning, plans, and construction
-    Big developments
-    Construction of complementary systems (e.g., sewers)
-    Aggregate impact of multiple small developments


Social Impacts
-    Social equality
-    Forcing, leading, or following social change
-    Meeting the needs of special classes
-    Quality of life
-    Community size and induced traffic


Synthesis
     Additional capacity has been a long-term tradition of corridor
improvement as a matter of professional and technical practice. 
While in some cases it has been extended extraordinarily by
political motivation and capacity beyond that necessary to serve,
current demand has been validated as a matter of prudent profes-
sional judgment.  Deciding when it is excessive is a product of
multiple factors beyond potential demand.  The issue at stake is
defining excessive capacity in an era when our social, economic,
and institutional capacity is far lower  it may have been in the
past.  The degree to which we can estimate unneeded capacity and
develop a planning process capable of incorporating all the
necessary factors of excessive capacity is the key contemporary
challenge.  A supplementary challenge is including new, influential
actors in the decision process and anticipating major socioeconomic
forces as capacity is added.


Key Questions
-    To what extent is the corridor development planning process
     capable of anticipating all the possible actors that should be
     included?
-    What kind of forecasting should be done to anticipate the
     influences of economic change, technological forecasting, and
     social change?
-    Should the nature of the Metropolitan Planning Organization
     process be changed to broaden its membership and focus beyond
     traditional participants' concerns?
-    Does comprehensive and/or land use planning hold the key to
     mitigating the consequences of additional capacity?
-    Should financing be separated institutionally from capacity
     design and construction?
-    Are there better mechanisms for identifying the non-transport,
     non-spatial benefits of transportation improvements?

102   Appendix





Environmental Effects of Added Transportation Capacity

John H. Suhrbier
Principal, Cambridge Systems, Inc.

Summary
     The importance of environmental considerations in developing
added transportation capacity continues to increase.  The
preparation of environmental impact statements may have become more
routine over the last 20 years as experience with impact analysis
methodologies has become more sophisticated.  The influence of a
wide range of environmental and community concerns on the outcome
of actual decisions, though, has both increased and become more
complex.  This is seen in both the kinds of transportation
alternatives that are now being examined and in the additional re-
quirements that are being placed on travel demand forecasting
methodologies.  In particular, significant attention is being given
to travel demand management strategies and to the development of
intermodal facilities for the movement of freight and people.
     The Clean Air Act Amendments of 1990 (1990 CAAA) represent an
important example of environmental influences on transportation. 
The requirements of conformity of air quality and transportation
plans are receiving considerable attention.  However, there are
other important analytical implications of the 1990 CAAA.  These
include the preparation of spatially and temporarily disaggregated
emissions inventories; the monitoring of emissions, congestion,
vehicle miles traveled (VMT) and vehicle occupancy rates, and the
ability to analyze the effectiveness of pricing and other market-
based economic incentives.  There is a need to improve the
interface between transportation and emissions models, especially
with respect to the prediction of accurate estimates of vehicle
operating speed and acceleration.  In addition, trip rather than
VMT-based emissions estimates are needed.
     Air quality transportation analyses traditionally have
focussed on mode choice impacts.  Metropolitan areas, however, are
increasingly examining a variety of land-use and growth management
actions in concert with the development of new or expanded
transportation facilities.  This is resulting in the need to
examine the influence of new transportation infrastructure on the
patterns of housing and employment location.  In support of these
associated analysis requirements, interactive land use/
transportation model systems increasingly are being employed.
     There is also a recognition that environmental considerations
must be given increased weight in the development of transportation
system plans and in the prioritization and programming of
individual projects.  This is necessary to respond not only to the
broader range of policy concerns but also to the increased funding
flexibility, strengthened regional decisionmaking, and the desire
to address tradeoffs between preservation and increased capacity.
     In brief, the attention being given to issues such as
congestion management, air quality, downtown revitalization,
airport access, and growth management is resulting in a need to
enhance current transportation analysis and modeling capabilities. 
Many short-term improvements are possible, including incorporation
of better interactions among the traditional four-step models. 
More fundamentally, there may be a need for an entire new
generation of travel demand model systems.  Building upon a
geographic information system foundation, 

                                                     Appendix   103





these systems would reflect an expanded range of policy
sensitivity, disaggregate or market segment forecasting approaches,
and incorporate the influence which added transportation capacity
may have on developed patterns.

104   Appendix





Use of Travel Forecasting Models to Evaluate the Travel and
Environmental Effects of Added Transportation Capacity

Daniel Brand
Charles River Associates

Introduction
     While significant additions of highway capacity have slowed in
major metropolitan areas over the last two decades, a number of
important construction and widening projects are still being
considered.  However:
     Almost by default, environmental regulations - and the
     relentless advocates who use them most effectively - have
     begun to dictate the physical shape and priorities of the
     region.  From the most ambitious bridges to the smallest
     playground, from airports and highways to shopping malls and
     boat slips, legal requirements and protests rather  planning
     now orchestrate nearly every decision a builder or government
     can make (Specter 1991, B1).
     The 1990 Clean Air Act Amendments (1990 CAAA) require explicit
consideration of whether adding transportation capacity produces
more, rather less, air pollution.  Indeed, they establish the
principle of regional emission budgets and conformity to the emis-
sion reduction schedules contained in State Implementation Plans
(SIPs).  With the important exception of UMTA's Alternatives
Analysis cost-effectiveness requirement for major transit
investments, the 1990 CAAA requirements appear to be the first
significant substantive effectiveness standard by the federal
government for new transportation projects.
     The principle that travel volumes increase as travel is made
easier by adding transportation capacity is well established.  More
specifically, the conference organizers state:

          The question being increasingly raised is whether adding
     capacity is producing more, rather  less, air pollution. 
     Current transportation practice generally assumes that adding
     transportation capacity relieves congestion, reduces delay,
     permits travel at more efficient speeds, and therefore reduces
     air polluting emissions.
          Few (if any) existing trip generation models consider the
     effects of added capacity to stimulate new travel.  The
     effects of increased trip distance and mode shift may be
     accommodated by current travel forecasting and growth
     allocation models.
          It is clear however from recent legal proceedings that
     business as usual for assessing the effects of roadway
     improvements on air quality will no longer be acceptable. 
     Future air quality assessments will have to determine whether
     the potential emissions reductions attributable to improve
     speeds and delay win exceed the additional emissions possibly
     generated by induced traffic.  This poses the possibility that
     all traditional trip generation models, and perhaps other
     models as well, may have to be revised.  It is critically
     important to increase understanding of the effects of added
     capacity on all aspects of travel and to decide if and what
     improvements to forecasting procedures are necessary in order
     to accurately assess the air quality effects of added
     transportation capacity.

                                                     Appendix   105





     The purpose of this presentation is to discuss and recommend
improvements to travel forecasting procedures which are required
"to accurately assess the air quality effects of added
transportation capacity."

Shortcomings of Current Urban Travel Forecasting Models
     It would appear that we have come to the end of the era of
assuming fixed trip tables, and even fixed loading points, as in
the case of the West Side Highway Project (WSHR) travel
"models"which assumed no change in Hudson River bridge and tunnel
volumes between all WSHR alternatives, including the no build. 
Clearly, a fixed amount of travel on a currently congested highway
(or highways across a screenline) will result in better air quality
as capacity is added.  However, it would appear that such analyses
are no longer acceptable under the 1990 CAAA, if they ever were.
     In general, the shortcomings of today's travel forecasting
models in the context of the 1990 CAAA have been known for many
years.  Twenty years ago, this author wrote:
          Current practice in predicting quantity of travel on
     transportation networks is based on the theory of equilibrium
     between supply and demand on the transportation network.  That
     is, there should be an equality between the travel conditions
     found (such as times and costs) on the loaded network and the
     travel conditions used as input to the prediction.  The
     current procedure is to model travel behavior as a series of
     sequential, independent chokes of trip generation, trip
     distribution, modal split, and c (route) assignment.  Land use
     forecasting precedes travel forecasting as a separate step. 
     For each travel choice, the existing pattern of usage in the
     region at the prevailing equilibrium between supply and demand
     is related to a small set (often one) of independent
     variables.  The trend or description is then assumed to hold
     in the future.
          For example, trip distribution is modeled as a function
     of a simple description of trip lengths that prevailed at the
     equilibrium between supply and demand represented in the base-
     date data file.  The usual trip-generation procedure relates
     total trips in and out of a zone only to measures of the
     activities existing in the zone.  The assumption is made that
     total travel, as measured by trip ends, varies only as
     development varies, not as conditions on the tested networks
     change.
          In addition, there are computational and logical
     difficulties in bringing the predicted travel conditions into
     line with the conditions (if any) used as input to each of the
     component travel choice models.  There is no assurance that
     travel times and costs resulting from traffic assignment win
     equal travel times and costs explicitly or implicitly input
     into each sequentially applied model of component travel
     choice - that is, that an internally consistent network
     equilibrium will be produced.
          One may reflect that the urban transportation studies in
     the 1950's and the 1960's took the easy way out by equating
     usage (a constant) with demand in calibrating models.  For
     existing conditions, the models fit well with usage.  Not
     generally recognized was that present usage is merely a fixed
     quantity of travel demanded at existing levels of supply,
     accessibility, and benefits from the opportunities at existing
     trip ends.  The simple trends of descriptions contained in the
     conventional models cannot be predicted forward with much
     confidence in a situation as complex as travel wi an urban
     region.
          The shortcomings of the conventional models increase when
     predictions are made of travel on congested networks (i.e.,
     when small changes in assigned  travel volumes result m large
     changes m link travel times and delays).
          Since large-capacity, relatively congestion-free
     expressways in high-density urban areas are increasingly
     difficult (if not impossible) to build in the era of urban
     high-

106   Appendix





     way controversies, we can look forward to the future
     equilibrium between supply and demand being quite different
     from that which existed in the early I%Os when most of our
     large-scale transportation study data collection took place. 
     Society's changing values introduce new conditions and
     information requirements in the transportation modeling
     process.
          Operationality in transportation planning today requires
     demonstrating how smaller transportation systems accommodate
     smaller amounts of travel and how greater systems accommodate
     greater amounts of travel.  Savings in resources expended by
     travelers (i.e., user benefits) from transportation
     improvements must be accurately calculated and vary
     appropriately with the total resources expended by society to
     provide those benefits.  The latter resources, which are
     increasingly high valued by society, include air and noise
     pollution, safety, community disruption and many other effects
     that are external to the calculation of travel demand in a
     predictive model.  Accurate travel forecasts are needed to
     calculate their magnitudes.
          Only by explaining the causal relations underlying travel
     demand can accurate forecasts be made of future changes in the
     performance of a transportation system as land uses and
     transportation facilities change.  Emerging values and
     information requirements of transportation decision makers
     require policy-sensitive demand models in transportation
     planning (Brand 1973, 10-11).


Why New Highways Increase Travel
     In theory, any addition of transportation capacity that
reduces the times and costs of travel will cause people to consume
more travel.  Travel decisions involve a series of tradeoffs people
make between the times and costs of travel on all available
alternatives and the benefits of travel at the trip ends.  Figure 1
illustrates the supply/demand mechanism which governs this
behavior.
     Until now, our experience with changes in travel choice
behavior has been derived primarily from travel responses to
transportation improvements.  These improvements have enlarged the
area within which individuals travel to obtain benefits at the trip
end.  The past few decades in urban transportation have been
characterized by high capacity, high speed transportation
improvements such as expressways and high capital rail transit
systems and extensions.  These have made possible travel and
settlement on new land which has been incorporated into our
metropolitan areas.  These investments have also merged and fuzzed
the boundaries between suburbia and settlements in rural areas
outside the metropolitan areas.  Obviously, the effects of these
most recent investments in urban transportation are still shaking
themselves out
     For better or worse, our major transportation investments,
which have increased labor productivity and economic development,
have sown some of the seeds of their own failure, as is so often
the case in our complex economic system.  Our success in increasing
real incomes in our society through transportation and other
economic investments has resulted in increased demand for housing
to improve our standard of living.  The well-known result of this
is that higher real incomes lead our urban populations to move
farther out from the center of our cities because there they can
consume more housing and land, as well as more travel, at a lower
total cost for the entire package.  Until now, the added utility of
cheaper land, housing, and green grass farther away from our city
centers has been greater for our more affluent urban population 
the added disutility of the transportation cost of traveling to and
from their dispersed housing, employment, shopping, etc.
     However, we may be faced with a situation where congestion is
increasingly out of control in our metropolitan areas.  The
automobile/highway system is a classic example of a

                                                     Appendix   107





system characterized by individual choice behavior that puts
private interests over the public interest.  Every time a person
drives a car onto a congested roadway, far more aggregate delay is
imposed on others - on the system than on the driver.  This
aggregate delay on others results in far more air pollution and
energy consumption by others  by the individual who is causing the
delay and pollution.  In economic terms, the marginal private cost
of highway travel is much less than the marginal social cost of
travel on the already congested highway system.  In fact, the more
congested the highway corridor, the greater the difference between
the marginal social and marginal private costs of making a trip by
auto (De Corla Souza 1990).
     Congestion is a price the system imposes as a result of
private decisions to locate in sprawling regions and on larger
plots of land, farther away from work and shopping.  And as we
decide to spend increasing amounts of money on housing, we don't
know the transportation price our decisions impose on everyone
else.  We invest heavily in expensive housing without confronting
the total cost of our location decisions.  This leads to real
inefficiencies; the system has lost its ability to confront
consumers with the real costs of their decisions.  This is as true
in the long-run for our land use location decisions that generate
congestion as it is in the short-run for our individual travel
decisions.
     There are reasons that new transportation investments
accompanied by better information for travelers can result in less
congestion and added travel  without  features (Brand 1992). 
However, in general, except for some very special circumstances,
new transportation capacity that makes travel "easier" will
increase travel.  The question remains: will the increased travel
result in increased air pollution?


The Role of Forecasting Models in Evaluating Air Quality
     Clearly, improved travel forecasting models are available and
wi the state of the art to accurately assess the air quality
effects of added transportation capacity.  No one should doubt that
improved forecasting models are the principal way to address this
question.  Since travel in a metropolitan area is influenced by
many factors which change at the same time, direct observation of
the effects of changes in individual causal variables that may
affect the dependent variables of interest (i.e, travel and air
pollution)is necessary.  The problem is to specify and structure
these models properly.
     Planners should be aware that the travel forecasting
techniques used in transportation planning for the last 30 years
have their own implicit rules of behavior.  Behavior rules include
not only those implied by the independent variables included (and
correlations between these and variables not included: the
unobserved attributes); the changes described by the data (e.g,
behavior on new versus developed land, direction of change, cross-
sectional versus time series data); and the estimated coefficients
with their assumptions on the distributions of tastes in the
population; but behavior rules also include those on the structure
of the travel choices (e.g., the sequence of choices) and choice
alternatives (e.g., alternative destinations) over which the models
are applied.  A better and broader understanding of the rules of
behavior embedded in current travel forecasting ques(e g., trip
generation equations, gravity and logit models) is needed among
planners.  A full understanding of the choice structure implied by
the models being used can help in using models efficiently and in
selecting appropriate forecasting models.  Lack of knowledge of a
model's implied choke behavior may lead to grievous errors in its
application.  Examples of such problems with existing models and
their consequences will be given m the presentation.

108   Appendix





Specific Recommendations

     Ultimately, an accurate assessment of the air quality effects
of adding transportation capacity can be made only with travel
models which are properly embedded in the long run -general
equilibrium models that explain how land use and travel vary
simultaneously with added transportation capacity.  Only these
models can control for (hold constant) all the other factors that
affect travel (assuming they have been estimated properly).
     Such ultimate general equilibrium models may seem like too
tall an order - too far to reach - even in this national
conference.  However, we need look no farther  the last large
research project to investigate the relationship between
transportation supply and added travel to realize our problem:
          Although the researchers have concluded that there is a
     highway supply relationship, this relationship is not direct. 
     A complex causal change exists: highway supply changes bring
     about travel time and cost (level-of-service) changes, which,
     in turn, effect travel pattern changes.  In the short-run,
     travel patterns and levels of service interact, resulting in
     an equilibrium.  In the long run, the short run changes (with
     many other factors) influence future land use patterns.  These
     land uses influence travel patterns, which must again reach an
     equilibrium by interacting with highway levels of service.  In
     both the short run and the long run, VMT levels exist as one
     of many aggregate measures of the impacts of the highway
     supply changes.
          The complexity of this causal linkage between highway
     supply and VMT has two important consequences: first, the
     direction of VMT changes because a given highway supply change
     can vary; second, there are many variables that affect both
     the direction and the magnitude of VMT changes (NCHRP 1980,
     2).
     This research project attempted to measure the VMT impacts of
two major highway additions in the San Francisco region - with
inconclusive results.  The research was never formally published.
     The first recommendation, therefore, is to carry out further
research in this area, including the development of land use or
general equilibrium models.  These would enable the prediction of
land use and travel simultaneously as these are determined by a
given transportation system - improved over today's - and by the
many other determining factors which will be described at this
conference.
     The second recommendation is that we should be forecasting
travel in urban areas, not with trip generation equations that are
insensitive to travel conditions (as per the shortcomings of current
forecasting models cited above), but with direct demand models
which are valid descriptions of travel demand, given a fixed land
use distribution (Domencich 1968, 64).  Direct demand models
forecast travel directly by mode between origins and destinations
(perhaps, even by time of day) as a function of the activity
systems at the origins and destinations.  The price and service
conditions are forecast by the mode and all its substitutes.
     Direct demand models are themselves simplifications of the
general model.  They are partial equilibrium models which describe
how part of the system behaves in order for it to be in equilibrium
with the rest of the system Thus, we model the behavior of the
trip-maker who considers all trip-end opportunities fixed.  This
doesn't necessarily mean that this separation is at fault It only
means that:
-    The long-run models must be structurally valid, and
-    The short-run models should incorporate relations among travel
     and its determinants that are expected to remain valid in the
     future.
     Examples of how the current, sequentially applied travel
models (e.g., trip generation, distribution, etc.) violate the
second condition were given above under "Shortcomings."
     Regardless of whether they describe full or partial
equilibria, the air quality forecasting

                                                     Appendix   109





travel models must also contain appropriate supply/demand
equilibration mechanisms that measure that the changes in travel
times and other measures of system performance that give rise to
travel (as input to the model) are the same as those produced by
the model.  This congestion sensitivity is the only way to test the
assumption we generally make today "that adding transportation
capacity relieves congestion, reduces delay, permits travel at more
efficient speeds, and therefore reduces air polluting emissions."
     The third and final recommendation is that we need
considerable research and development of improved (structural)
travel demand models which are sensitive to the great number of
"non-traditional- transportation improvements called for under the
1990 CAAA.  Specifically, Section 108(f) of the 1990 CAAA lists and
describes 16 transportation control measures (TCMS) which have been
described in an EPA guidance (EPA 1991).  Since these TCMS, in many
cases, involve constraining highway travel, we know very little of
their effects on travel.  Considerable travel modeling work in this
area is needed to be able to forecast the contribution of these
TCMs to meeting the air quality objectives of our SIPS.

110    Appendix





Click HERE for graphic.

                                                     Appendix   111





References
Brand, Daniel.  "Intelligent vehicle highway systems: A smart
choice for travelers and society." TR News, p. 160, May/June 1992.

"Theory and method in land use and travel forecasting." TRB Record
422, pp. 10-11, 1973.  DeCorla-Souza, Patrick.

"Suburban/urban transportation investment: What will it cost and
how will I pay?" U.S. Federal Highway Administration, 1990.
Domencich, Thomas A., Gerald Kraft, and jean-Paul Valette.

"Estimation of urban passenger travel behavior: An economic demand
model." Highway Research Record 238. p. 64, 1968.

NCHRP Staff Digest of Project 8-19.  "The vehicle miles of travel:
Urban highway supply relationship."

Cambridge Systematics and JHK & Associates, p. 2, December 1980.
Specter, Michael.  "Environmental rules: How they dictate region's
agenda." The New York Times. p. B1, November 25, 1991.

U.S. Environmental Protection Agency, Office of Mobile Sources. 
Transportation control measure information documents (Draft), by
Cambridge Systematics, Inc. et al.  Ann Arbor, MI.  October 1991.

112   Appendix





Travel and Locational Impacts of Added Transportation Capacity
Experimental Designs

Peter Stopher
Director, Louisiana Transportation Research Center and Professor of
Civil Engineering, Louisiana State University


Introduction
     The purpose of this paper is to explore experimental designs
for measuring the travel effects of adding transportation capacity,
particularly to a congested transportation system.  Theory had
deduced that nine potential effects may arise when capacity is
added to a congested travel corridor (Stopher, 1992; Harvey and
Deakin, 1991).  Briefly, these effects or impacts are:
-    Route changes
-    Mode changes
-    Trip timing changes
-    Destination changes
-    Trip frequency/trip chaining changes
-    Auto ownership changes
-    Residential location changes
-    Employment location changes
-    Regional growth changes in either or both population and
     employment
     It is important to distinguish that the first five of these
are likely to be short- to medium term changes, taking place
anywhere from the day of opening of the new capacity to sometime
probably within the first one to two years from the capacity
addition.  On the other hand, the latter four changes are likely to
be medium- to longterm, with most effects showing up at least one
or two years after capacity addition and up to maybe ten years or
more later.  This means that the first five changes may be com-
paratively easy to measure in relation to either an actual capacity
addition or a description of a possible capacity addition, while
the latter four are likely to be comparatively difficult to mea-
sure.  The measurement difficulties for the longterm changes will
arise in large part from the fact that, as more time passes, other
events and changes quite distinct from the capacity addition will
cause changes in each of auto ownership, employment and residence
locations, and overall regional growth.  These will include family
life-cycle changes; cyclical changes in the local, regional, and
national economies; new technologies; changing values; and both
manmade and natural disasters.
     One might also argue that if it is necessary to spend ten or
more years to determine if certain of these effects take place and
ascertain their magnitude, this may be much too late to impact the
investment decisions being made in the next several years.  Such an
argument suggests a redundancy m measuring long-term effects of
this nature.  This author would, however, disagree with such a
notion, in that the then - current problems, the nature of which is
as yet uncertain, may well be a result of actions taken in years
preceding, so that such a longterm study will illuminate much in
the causality of transportation problems.  Therefore, this paper
will consider the potential to measure even quite long-term
effects, even if a decade or more is required for measurement The
issues to be addressed are much more concerned with how to account
for the time-dependent aspects of the externalities than with the
total length of time, per se, that may be required for measurement.

                                                     Appendix   113





     Two additional context issues are important to consider. 
Stopher (1992) has argued that most of the effects of added
capacity that are the focus of this paper will occur in urban areas
or major corridors of urban areas that experience congestion that
is significant in both duration and geographic extent.  Thus, in a
system that is largely un congested except for a specific capacity-
related bottleneck, most of the effects are unlikely to occur or
are likely to be very small in magnitude.  Second, much of the
theory and anecdotal information that supports the contentions that
capacity increases cause the array of effects described earlier in
this introduction, maintains that the effects are substantially
more significant in larger urban areas than in smaller ones (Remak
and Rosenbloom, 1976).
     Thus, any experimental design should preferably be focused on
larger urban areas (perhaps those with at least 1 million popula-
tion) and also on those where congestion is fairly widespread in
time and along at least two or more significant transportation
corridors.  However, to the extent that resources may allow, it
would be of considerable value to perform the experiments in
several locations (at least four), so that variability in size and
extent of congestion could be included.  The minimum of four
locations is suggested on the grounds that:
-    Two points always lie on a straight line, so that no
     significant conclusion could be drawn from two locations and
-    While four points are still inadequate for statistical
     significance, they allow sufficient variability to determine
     if effects may be postulated to vary with either population or
     extent of congestion.
     It is also appropriate to note here that measurement of the
types of changes theoretically expected as a result of capacity
increases may be done without any such capacity increases being
undertaken.  The arguments that define the impacts of capacity
increases are mirror-image arguments about how people re-- ac-t-to
increasing levels of congestion.  If one is willing to assume that
this reversibility principle holds, then it is possible to measure
the context of increasing congestion and how people respond to it. 
Thus, if nearer destinations are substituted for farther ones,
trips become chained or rescheduled, people shift from using the
car to using public transit, and, in the longer run, auto ownership
is decreased; and home or workplace is relocated to reduce the
travel time involved in commuting.  It may be concluded, then, that
each of these changes is potentially reversed when a capacity
increase is provided.  This notion is used in considering the
experimental designs that follow.
     This section elaborates on the experimental design that would
result from the comprehensive strategy.  The next section outlines
three possible generic approaches to the experimental design.  The
following three sections take each of these experimental designs,
elaborate on them, and review the pros and cons of each.  The sixth
section of the paper suggests a comprehensive strategy that
combines elements of each of the three approaches.  This section
elaborates on the experimental design that would result from the
comprehensive strategy.  The final section draws conclusions that
represent initial possible recommendations on the experimental design
that could be implemented.
     The paper is intended to be a resource document that will
provoke new thinking and discussion.  Therefore, it is not intended to be
exhaustive on possible experimental designs but, instead, to deal
in depth with three different designs that may help illuminate both
the opportunities and the problems.  It is the author's hope that 
three designs and the comprehensive strategy will serve to set
others thinking and may produce yet other, more effective designs.


Review of Approaches
     Three categories of experimental approach are considered in
this paper.  Each approach has certain strengths as well as certain
weaknesses as many as possible of which should be explored.  A
combination of approaches may offer the strongest experimental
design because of

114   Appendix





the ability of such a strategy to offset weaknesses of the
individual approaches, and also to offer some instances of two or
more ways to measure the saran effect.  Three approaches considered
in this paper are:
-    The case study
-    Attitudinal and preferential surveys
-    Longitudinal panel surveys
     In the remainder of this section, a brief description of each
approach is provided.  The following sections then explore the
strengths and weaknesses of each.


The Case Study
     The case study involves selecting a corridor in which a
capacity expansion is to be provided.  The approach would involve a
before study to determine travel patterns in the currently
congested corridor, followed by a series of after studies spanning
several years to obtain data on changes arising from the capacity-
expansion project.  The samples for the before and after surveys
would be drawn not only from the immediate vicinity of the project,
but also from a larger study area wi the potential influence area
of the project.  Surveys would most likely be conducted on both
residents and businesses within the total study area.  The surveys
would be expected to report on revealed preference for residents
and businesses alike, i.e., providing data on what people and
employers currently do in relation to choices involving each of the
issues of concern in capacity expansion and congestion.


Attitudinal and Preferential Surveys
     With the attitudinal and preferential approach, a number of
distinct surveys can be included.  The approach can be used without
an actual capacity expansion project, although use in conjunction
with a project may be desirable.  Among the included surveys are
focus groups, attitudinal surveys of both residents and employers,
and stated preference surveys of residents and employers.

     Focus groups could be conducted with groups of residents and
employers to determine the extent to which congestion impacts their
choices relating to destinations, modes, time of day, location,
auto ownership, etc, and whether or not such choices are
potentially affected by a change in the congestion levels as would
occur when capacity is added.  Building on the results of such
focus groups, attitudinal surveys could be designed that would
measure congestion and capacity-increase impacts on travel,
location, and auto ownership on psychological scales of importance,
propensity to change, etc.  A more quantified approach would result
from designing stated-preference surveys of residents and
employers, based on the focus groups, and offering the standard
types of trade-off questions in a stated-preference design.  Such a
survey could be conducted in a variety of locations and at
different times to produce a more extensive array of responses on
congestion and capacity-increase effects.


Longitudinal Panel Surveys
     A longitudinal panel survey would be undertaken in at least
one of two ways: either an actual capacity-increasing project
situation in which the panel is initiated prior to the project and
continued for several years after; or using a selection of areas
where congestion is changing and determining how panel behavior or
attitudes and preferences change over time as congestion also
changes.  An important aspect of a longitudinal panel is that it
would, in this case, follow residents and employers who move away
from the location where they were when the panel was initiated. 
This would be important as a means to determine the extent to which
relocation solved the problems arising from congestion.
     Panel surveys could use either revealed preference measures,
stated preference measures, attitudes, or a combination of any or
all of these methods.  Revealed preferences would be more
instructive in panel surveys compared to

                                                     Appendix   115





one-shot surveys, because of the ability to measure the dynamics of
prior changes.


The Case Study Approach
     The case study approach involves identifying a location where
a capacity-increasing project is to be constructed and conducting
at least one before survey, followed by a series of after surveys. 
The surveys would be directed at both residents and employers to
determine the extent to which the congestion existing prior to the
capacity addition has impacted specific decisions relating to
travel, activities, and location; and then to measure how the
relief of that congestion impacts those same decisions sub-
sequently.  The notion of a case study is clearly to rely, to as
great an extent as possible, on the measurement of revealed
preferences.  In other words, the issue is to determine the actual
behavior before the project and then to measure changes in behavior
after the project.
     At first glance, this approach appears to be the most obvious
and sensible one to measure the effects of a capacity increase. 
However, once actual design issues are confronted, it becomes much
less apparent that this is a workable approach.  The first issue to
be dealt with is the definition of the populations of residents and
employers from which the sample should be drawn.  If the population
is defined as those residents and employers who are located within
the corridor of the project, even where the corridor is defined
quite broadly, this will lead to inclusion of a number of residents
and employers who will not be affected by the project.  At the same
time, there may be many residents and employers who would not be
included in any definition of the transportation corridor who are
impacted considerably by the project.
     The second issue is that the before sample should be drawn so
as to include residents and employers who may not use the
transportation corridor before the capacity increase (because
congestion has made opportunities reachable through that corridor
too unattractive to be considered), but who will use the corridor
after the project is completed.  If the contention holds that
capacity increases in the transportation system lead to the
relocation of homes and workplaces, then there is a third group
that cannot be captured in the before survey, representing those
who move into the corridor subsequent to construction of the
capacity increase.
     None of these sampling issues is completely insurmountable. 
As is discussed in more detail later in the paper, some combination
of cross-sectional and panel surveys might serve to resolve some of
these problems.  Nevertheless, very significant sampling issues
remain, particularly in defining the extent of the geographic area
from which to sample, the means to identify in the before survey
those who will be affected after construction, and the potential
implications for random sampling that some very large samples may
be required in Order to include a significant number of those who
exhibit impacts from the project.
     The next issue relates to the time frame of measurement.  As
has already been noted, a number of the impacts that are theorized
to occur are of long-term impact.  This implies that measurement
should continue for several years in the after period.  The problem
presented by this is that of externalities. it is unlikely that the
residents and employers in the project area will be unaffected by
any other transportation System changes over the several years that
measurements should take place.  However, determining which impacts
follow from the construction of new capacity and which follow from
the variety of other transportation system changes taking place is
likely to prove extremely challenging.  Consider the case of the
construction of the Century Freeway in Los Angeles, for example. 
Assuming one can surmount the sampling problems to select an
adequate sample for the before and the series Of after surveys,
within one or two years of the opening Of the freeway, it can be
expected that the light rail facility along the freeway median will
commence operation.  There is also a plan to add other rail
projects in the vicinity of the freeway, such as the Coast Light
Rail Line, extensions of Metro Rail to the confluence of the
Century and

116   Appendix





Santa Ana freeways, and the potential addition of HOV lanes to
several freeways in the area.  While all this proceeds, it is
surely improbable that automobile fuel prices will remain un-
changed, or that transit fares will remain fixed.  Other changes,
such as new technologies for the automobile, response to clean air
legislation, and the like will all impact travel behaviors and
location in some form or another.  The challenge will be to control
for these externalities in order to have a clear measurement of
precisely how the capacity addition, represented by the new
freeway, had an impact on travel patterns and household and
employer decisions in the years following its opening.
     Finally, the case study approach relies on the measurement of
change.  The issue here is that change must be measured relative to
something.  In actuality the question being addressed by the
experimental design is to determine changes that take place as a
result of the addition of capacity, which implicitly mean changes
that are different from those that should have occurred without the
change in capacity.  This raises the real nub of the case study
approach.  There is no question in this author's mind that the
various surveys that could be conducted on a case study of capacity
increase will measure change in travel behavior: travel behavior is
highly dynamic and results in continual changes.  The issue is to
determine that changes have taken place that are different from or
greater  those occurring without the capacity increase.  Further,
if the contention made by several recent papers that peak period
travel seems to continue to increase, despite increasing congestion
(Fleet and DeCorla-Souza, 1991), the issue becomes one of
determining how behavior would have changed without the project,
and comparing that to the changes that occur with the project.
     This issue of the relativity of change suggests that the
requirement would be to find a similar transportation corridor in
which no capacity increase is planned, but where congestion levels
are identical in the before period.  Next, a panel study would be
conducted to determine the changes that occur in that corridor. 
The impacts of the capacity increase are then measured by the
differences between the two study areas.  It is beyond the scope of
this paper to define the measures of similarity that must be used
to select the null corridor, but this is clearly a significant
challenge in itself.
     In considering this approach, one is reminded of the studies
that took place in the 1970's, in particular, that endeavored to
measure the impacts of transportation on land use (the Lindenwold
Line and others - Boyce, 1970, Demetsky and Shepard, 1972 inter
alia).  These also took place in a case study context and seemed to
be universally unable to substantiate the actual extent of changes
caused to land uses by the addition of new transportation capacity. 
Issues such as the impacts of uncontrollable externalities and
isolation of a control location against which to measure change
were among the principal reasons behind the failure of these
efforts to measure, with any degree of certainty, the impacts of
transportation facilities on land use.  In the debate on what
impacts capacity increases in the highway system have on travel
patterns, locational decisions, and growth, those maintaining that
many of these impacts do not occur rely on these failed studies on
land use to support that position.  In actuality, the studies did
not establish the lack of a linkage between land use and
transportation but simply failed to find it because of the mea-
surement and experimental design problems.  This should emphasize
the need for care in designing experiments for the capacity-
increase issue.


Attitudinal and Preferential Surveys

     The difficulties alluded to for the case study approach give
rise to the idea that other methods need to be examined as offering
a potential alternative in which uncontrollable externalities,
control situations, and sampling difficulties might have less
impact.  As noted earlier in this paper, attitudinal and preference
approaches include a number of measurement

                                                     Appendix   117





methods and procedures, including focus groups, attitude surveys,
and stated preference measurement In this Section, each Of these
broad categories is considered further in terms of what can be
measured and in what situations, to determine if they offer
alternative methods to the experimental design of the case study
approach.


Focus Groups
     Focus groups do not provide a means to measure the impacts of
capacity increases.  However, they do provide a means to determine
what decisions people believe are impacted by congestion or by an
increase in capacity and should be a precursor to any field study
of impacts.  In this case, the experimental design would be based
on selecting several groups of people to participate in independent
focus groups, considering the issues of congestion and congestion
relief.  Focus groups could be drawn from various different
categories of workers (e.g., by income, auto ownership, etc.),
different family groups (to determine interaction between family
members' decisions), and employers with varying employee types.
     Each focus group would be asked to consider the issue of the
way in which congestion impacts what they do and how they organize
their lives.  They would be asked to consider how they would react
to continued increases in congestion levels and then how they would
react to the provision of new capacity in a congested corridor. 
Such focus groups would serve to provide an initial test of
hypotheses about the impacts of capacity increases and would also
provide detail on the specific "s of decisions that are impacted. 
They would be the precursor to any of the other attitudinal and
preference measurement methods discussed in this section.
     Three advantages stem from the focus groups.  They are
independent of externalities, since the nature of the focus group
is to focus on the specific set of issues of concern.  Second, they
need neither an actual capacity-increasing project nor a control
corridor in which measurements would be taken.  Indeed, they offer
the potential to draw similar focus groups from congested urban
areas across the nation and thereby determine, further, if there
might be regional or other differences in response to congestion
and capacity increases that have not been hypothesized to date. 
Third, there are far less serious difficulties in selecting the
sample for inclusion in the focus groups, since the area of
influence of a specific project does not need to be defined.  A
potential qualification for inclusion in the focus group may only
be to establish that the individual experiences congested traffic
on reasonably frequent occasions, either on work trips or on non-
work trips.  It is dearly advantageous to determining the full set
of impacts to include those who experience congestion on trips
other than commute trips in order to determine a broader range of
responses to congestion and to potential capacity-increasing
projects.


Attitude Surveys
     Using the results of focus groups, attitude surveys could be
designed to measure, on psychological scales, aspects of response
to congestion and capacity increases that would result in an
initial decrease in congestion.  Attitudinal surveys can be
constructed to measure such constructs as importance, preference,
likelihood to change a behavior, and satisfaction, inter alia. 
Such surveys can be conducted on residents and employers, under
conditions of a case study, or under hypothetical circumstances. 
The focus groups would also be likely to provide information on the
pertinent descriptors of congestion and capacity increases.
     Because there is generally a fairly high degree of
unreliability in both reporting behavioral intentions and longer-
term responses to hypothetical (or even actual) events, the atti-
tude surveys would be most likely to measure the short-term
responses by residents to increasing or decreasing congestion. 
Attitude surveys, however, may be successful at determining likely
longer-term responses by employers, particularly because senior
manage-

118    Appendix





ment of a company is more accustomed to considering longer-term
responses and actions required by the company.  Experience in
interviewing employers in connection with Regulation XV in the
South Coast Air Basin of California showed a relatively high level
of responsiveness on the potential of increasing congestion to
generate changes in the way in which companies do business and
their choice of location.
     As with focus groups, one of the primary benefits of the
attitudinal measures is that they do not require a case study or
the identification of a control transportation corridors The pri-
mary disadvantage of such an approach is the limitations on what
can be measured and the reliability of measurement.  Potentially,
such techniques may have their greatest pay-offs in use with senior
managers of employers in congested areas where both short- and
long-term responses may be obtained more reliably.  The sampling
benefits mentioned for focus groups apply also to attitudinal
measurement techniques.


Stated Preference Surveys
     The third type of survey under this general heading, and the
one that probably has the greatest contribution to the travel
behavior of individuals, is that of stated preferences.  In a
stated preference survey, individuals are presented with a series
of trade-offs between attributes of alternatives that they may
consider choosing and are asked to indicate when attribute changes
would precipitate a change in current behavior to an alternative
behavior.  The key to an effective stated preference survey is to
design a composite set of trade-offs that allow reliable
measurement of potential behavior changes in response to a
particular type of event or system.
     Stated preference surveys are becoming the accepted method for
measuring likely ridership of new technologies, such as very high
speed ground transportation, and have also been used successfully
by researchers in Europe attempting to obtain improved measurement
of value of tin-se and value of certain types of accidents.  The
application of the technique to congestion and capacity increases
seems obvious, therefore.
     The design of the stated preference survey would again benefit
substantially from the focus groups, which should be considered as
a precursor for the design.  In this case, the focus groups would
not only provide information about the attributes to be used in the
preference measurement but would also provide inputs on the
description of the environment and the ranges of values of
attributes to use in the stated preference designs.
     Given uses that have been made of stated preference
measurement to date, it is not clear how reliably it will measure
longer-term changes in response to capacity increases.  However,
there is clearly no difficulty in including such options as
changing vehicle ownership and changing home or workplace location
as part of the instrument.  Unlike revealed preference measurement,
it is not necessary for the study to span the time period within
which such longer-term changes will be made in order to determine
the likely behavior changes that may occur.  Conducting the survey
over two or three years, in which changes in the actual transpor-
tation system experienced by subjects of the survey is tracked,
would provide increased information on the reliability of the
method.
     As with each of the methods described in this section, there
is no requirement for a specific case study of capacity increase
nor a control corridor; and externalities are controlled through
the questioning mechanism.  There are also no more complex sampling
issues  those already noted for selecting members for the focus
groups.  The measurement issues in this case revolve around
defining an adequate set of trade-off situations to measure
behavior changes that might follow from a capacity increase in
congested transportation corridors and to define behavior changes
likely under worsening congestion.  In addition, the stated preference
method is fairly extensive in questioning and may be less well-
adapted to use

                                                     Appendix   119





with senior managers of employers but will find its strongest
application with residents.


Longitudinal Panel Surveys
     While not necessarily a distinct methodology from the
preceding ones, the specific element of a longitudinal panel survey
of interest in this paper is its capability to measure change more
reliably  any other survey methodology.  In a panel survey the
underlying principle is to recruit a generally small panel of
individuals that may be drawn to represent different subgroups of
the population of interest and to survey the panels repeatedly over
a period of time.  Issues that arise in the execution of panel
surveys include replacement of panel members that leave the panel
and sampling issues relating to the initial recruitment of the
panel.
     By the nature of the panel principle, which is the measurement
of change, the likely method of measurement is that of revealed
preferences.  In other words, the panel members would be asked to
report on actual behaviors at each time of survey, from which
changes could be determined over time.  While measurement of stated
preferences or attitudinal data could be included in a panel
survey, the change measured in this case would be the stability of
the preferences, not the response to actual changes in the trans-
portation system.  Therefore, the panel should be considered first
and foremost as a revealed preference tool.
     A longitudinal panel could be used in two different ways to
measure the impacts of either congestion increases or capacity
additions designed to relieve congestion.  First, a longitudinal
panel could be set up within the context of an actual capacity-
increasing project in a congested area.  The advantages of the
panel are obvious compared to the execution of a series of cross-
sectional (i.e., independently-sampled) surveys.  In this case, the
panel would be recruited prior to the new capacity opening and
would be asked to report on actual behaviors for a period of time,
showing travel patterns under conditions of congestion.  After the
capacity increase has been completed, the panel would be surveyed
on a number of successive occasions to measure changes in travel
patterns and also to determine if changes take place in auto
ownership, workplace location, or home location.
     Unlike many panels conceived for transportation purposes, it
would be important in this application to continue to include
members of the panel who move, in order to track possible trade-
offs in transportation service that were achieved through the
relocation, and to offer some potential to include control measures
through panel members that move to a relatively uncongested
location.
     This application of a longitudinal panel, however, does not
resolve the issue of relating the amounts of change to what would
have occurred without the capacity-increasing project.  Therefore,
the requirement will remain for subgroups of the panel to be set up
in locations that have similar congestion levels in the before time
frame and no capacity-increasing project in the after period. 
Further, there would need to be similarity in the panel members
with respect to a variety of demographic and travel orientation
characteristics in order to measure the change caused by the
capacity increasing project.  In effect, there would need to be a
pairing of panel members, with each panel member in the case study
location having a counterpart with very similar characteristics in
a location where there is no capacity-increasing project and a
similar level of congestion.  Such a sample design, while not
impossible to achieve, will certainly be extremely time-consuming
and expensive to set up.
     The second potential use of the longitudinal panel would rely
on the reversibility notion of the changes resulting from capacity
increases.  Rather than being set up in a case study context where
a capacity increasing project was to be constructed, this
application would simply measure changes taking place as congestion
worsens.  Although this application would still require a control
location against which to measure how much of the change resulted
from increasing congestion, it may be possible to

120   Appendix





conduct this study effectively by choosing several locations in
which congestion exists at the outset of the study at very
different intensities.  For example, one subsample for the panel
might be selected from an urban area in which congestion is short-
lived and geographically restricted, and where the urbanized area
is not experiencing significant growth.  At the other extreme., a
subsample might be located in an area where congestion is
widespread, lasts for many hours, and the urbanized area is
experiencing rapid growth.  Additional subsamples may be located in
areas that lie between these two extremes.
     Panel subsamples would be required to match well on
demographic and travel characteristics, within the limits offered
by the varying types of urban areas.  However, , the sampling would
not need to be inclusive of all possible groups that might be
affected by congestion or capacity increases.  Rather, the panels
could be restricted to two or three primary demographic subgroups. 
If consistent results were obtained from each of the selected sub-
groups, generalizability to the entire population would be
feasible.
     In both applications of the panel survey, there would be a
need to include within the study design a comprehensive monitoring
of the transportation supply and costs in the vicinity of the panel
members.  This would be required in order to ascertain the extent
to which congestion changes during the study and to provide the
needed basis for correlating congestion levels with travel behavior
changes.  In addition, , it would provide at least a measurement of
potential externalities that may affect the overall measurement of
congestion-related changes.
     The panel survey will most likely apply to measurement of
those impacts affecting residents.  A panel survey of employers may
be an interesting proposition but may not find acceptability within
the target population.  Therefore, the most probable application of
this method is to residents of selected urbanized areas.


A Comprehensive Strategy
     So far, this paper has considered three distinct approaches to
the experimental design for measuring the impacts of capacity
increases on travel and location.  As has been mentioned several
times, however, these three approaches are not mutually exclusive. 
A real potential exists to combine elements of all three approaches
to produce a better experimental design, a design that may overcome
a number of the shortcomings that have been identified for each
approach alone.
     A comprehensive strategy should start out with the use of
focus groups.  The focus groups should target several different
groups of residents, including those who work outside the home and
those who do not, and should also include one or more groups of
employer representatives.  The focus groups would serve to
illuminate the specific elements of congestion and capacity
increases that may affect travel, locational, and related behaviors
and will also provide some insights on the attributes of congestion
and capacity increase to which people respond (e.g., time spent in
stop-and-go traffic, total travel time, unreliability and
instability of traffic flows, etc.). The focus group findings would
be used in the design of subsequent survey instruments, as well as
the sample design, itself.
     A combination of revealed and stated preference measurement
will provide the richness of data to identify what the impacts are
and by what magnitude these impacts cause changes in travel
decisions, locational decisions, and related decisions such as
vehicle ownership.  The particular appeal of stated preference
measurement is that it can be conducted with or without an actual
capacity-increasing project, and the externalities can be
controlled.  On the other hand, revealed preferences are the only
true measures of the actual behavior changes that take place. 
Therefore, some measurement of revealed preference is necessary to
validate the stated preference data and to test the hypothesis that
the changes indicated by stated preference and focus groups
actually do take

                                                     Appendix   121





Click HERE for graphic.


place.  In both cases, what to measure and in what units to measure
will be enhanced considerably by the results of the focus groups.
     Among the more difficult issues raised in considering the case
study approach were selecting a sample, identifying who is impacted
by a specific project, and finding a parallel control location in
order to determine the amount of change likely to take place
without the capacity-increasing project.  The combination of
revealed and stated preference methods offers a potential to avoid
each of these problems.  The presence of a capacity-increasing
project is not necessary, although it could be used in one or more
instances if such a project were available.  The survey would be
designed so that the stated preference portion would question
respondents about their responses to both worsening congestion and
alleviating congestion through a capacity-increasing project.  In
the event that none of the selected locations had a capacity-
increasing project, validation of the stated preference findings
through revealed preference measurement would concentrate on the
worsening of congestion.  The design would require, of course, the
concurrent measurement of actual levels of service on facilities
used or potentially usable by the sample in each location.
     Two other potentially appealing aspects to the combination of
revealed and stated preference measurements arise from the
implementation of these two methods within the third approach,
namely the establishment of longitudinal panels.  Clearly, the only
way in which changes in revealed preferences will be measured is
through repeated measurement in a longitudinal survey design.  The
use of panels is a method that provides much greater accuracy in
the measurement of those changes than can be obtained through the
repetition of cross-sectional surveys over time.
     The survey mechanism that is envisaged in this combined
approach is one that might consist of;
-    A survey of the demographics and other characteristics of each
     household and individual included in the sample;

122   Appendix





-    A stated preference survey of each individual covering a
     variety of changes in system performance that includes both
     increasing congestion and a scenario of capacity increase
     followed by an immediate improvement in level of service and a
     gradual subsequent degradation in service; and
-    A multi-day activity diary to measure actual behavior over at
     least three days.
     While it has been stated earlier that measurement of stated
preference through a longitudinal panel seems to be relatively
uninteresting, this changes when stated and revealed preferences
are measured together and also if certain changes are made in the
stated preference design.  Combining revealed and stated preference
questions in a longitudinal panel provides a richer base against
which to determine consistency of revealed preferences with stated
preferences and particularly enables review over time whether
actual behavior changed at a point indicated by the stated
preference data.  Second, the panels can be asked stated preference
questions on each repeat survey in which the options offered are
largely at different levels on each occasion but with sufficient
common ones to tie to the previous measurement.  If stated
preferences remain constant over time, as one would expect, this
design would both substantiate the stability of stated preferences
and provide, over a number of occasions, a far richer option set
than would be possible in a single survey.  If stated preferences
were to be found to change over time, then this approach would
reveal these changes and would provide additional insights on
adaptation behaviors and value system changes that may explain why
travel decisions are often harder than expected to influence
through system improvements.
     An advantage of the combined approach, undertaken in multiple
locations but without an actual capacity-increasing project, is
that the sphere of influence of a capacity-increasing project does
not need to be defined in advance.  Rather, the revealed and stated
preference methods would assist in defining the sphere of influence
by identifying the transportation corridors and the locations
within the urban area that residents would choose or avoid,
according to whether the questions relate to capacity increases or
increasing congestion.
     The focus of the above surveys is principally on residents of
the areas.  However, a very similar approach could be used for
employers in which revealed and stated preference measurements
could be undertaken with a panel of employers.  Many of the same
benefits of this combined approach would accrue for an employer
survey as for a resident survey.  The difference in this survey in
administration is that no diary is probably of use, and the re-
vealed and stated preference information may be obtained most
expeditiously in a face-to-face interview.  In addition, the
household and individual demographics would be replaced by a set of
characteristics describing the employer and its location.


Conclusions
     Several conclusions can be drawn about experimental design for
measuring the impacts of capacity increases in a congested travel
corridor:
-    A multi-year, longitudinal study is probably essential as the
     overall experimental strategy.  Measurement over several years
     will almost certainly be necessary because of the time needed
     to reveal various behavior changes.
-    A case study, comprising a location where a significant
     capacity increase is constructed, is probably neither
     necessary nor beneficial for the experimental design.  The
     impacts of external events, the difficulties of identifying
     the impacted population and sampling from it, and the
     necessity for a parallel control location all make the case
     study a very difficult and possibly unrewarding option.
-    The experimental design should use multiple locations with a
     common survey design and varying levels of existing conges-

                                                     Appendix   123





     tion. Preferably the sampled individuals or households in each
     location should be drawn from similar household and individual
     demographic characteristics.
-    Comprehensive measurement of performance of the transportation
     system in the vicinity of sampled households/individuals will
     be a key component of the study design.
-    The study design should include surveys of both residents and
     employers in the study corridors. The survey of employers will
     likely use different techniques from the resident survey but
     should be designed to be consistent with the survey of
     residents.
-    Conducting a series of focus groups should be considered a
     necessary pre-step before designing the survey and sample
     recruiting.  The focus groups will be asked to respond to
     scenarios of increasing congestion and then relief of the
     congestion through the addition of new highway capacity.
-    A combination of revealed preference and stated preference
     measurements seems likely to hold the greatest promise for
     both employer and resident surveys.  The use of stated
     preference is particularly important given an experimental
     design in which there is no capacity-increasing project.
-    The use of panels of individuals, households, and employers is
     likely to provide the most accurate tracking of change and
     provide the best basis for determining the validity of the
     stated preference measurement.  Continuation in the panel of
     panel members who move away is also important to the study, to
     determine to what extent the new location offers a real
     improvement in transportation performance levels (if any).

124   Appendix





References
1.   David E. Boyce.  Notes on the Methodology of Urban
     Transportation Impact Analysis.  Highway Research Board
     Special Report No. 111.  Transportation Research Board,
     Washington, D.C., 1970, pp. 41-44.
2.   Midiael J. Demetsky and Frank D. Shepard.  Measuring the
     Impact of a New Urban Highway on Community Traffic.  Traffic
     Engineering.  July 1972, pp. 42-45.
3.   Christopher R. Fleet and Patrick DeCorla-Souza.  VMT for Air
     Quality Purposes.  Paper presented to the ASCE Specialty
     Conference on transportation Planning and Air Quality, Santa
     Barbara, CA, July 1991.
4.   Greig Harvey and Elizabeth Deakin.  Toward Improved Regional
     Transportation Modeling Practice.  Paper presented to the
     National Association of Regional Governments Workshop on
     Transportation Planning for Air Quality, potentially
     Washington, D.C., November 1991.
5.   Peter R. Stopher.  The Impact of Capacity Increases on
     Congestion.  Paper presented to the 7th REAAA Conference held
     in Singapore, June 1992.
6.   R. Remak and S. Rosenbloom.  Peak Period Traffic Congestion. 
     Transportation Research Board Special Report No. 169. 1976, p.
     62.

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