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1.0 Introduction

The FHWA sponsored workshops on Traffic Data Quality (TDQ) in Columbus, Ohio, and Salt Lake City, Utah in March 2003. The primary objective of the workshops was to define an action plan to address traffic data quality issues. One of the foremost recommendations that came out of the workshops was the call for "guidelines and standards for calculating data quality measures.1 These guidelines and standards are expected to contain methods to calculate and report the data quality measures for various applications and levels of aggregation.

The focus of this project is to demonstrate how the concepts for defining and measuring traffic data quality can be implemented in practice. This includes the development of a framework to enable traffic data collectors and users to determine the quality of traffic data they are providing, sharing, and using. This report presents the framework and outlines methods for calculating the data quality metrics for different applications and illustrated with case study examples. The structure of the framework is summarized in Figure 1 which shows the steps to follow in assessing the quality of traffic data.

The intent is to develop a framework that is applicable to a broad spectrum of application areas such as ATIS; advanced traffic management systems; advanced public transportation systems; archived data management; traffic monitoring systems; and other applications dependent on accessibility to timely traffic information.

1.1 Background

Traffic data provide key indicators for a variety of transportation operations and planning purposes and in order to fulfill these purposes, the quality of traffic data must be assured. Traffic data for transportation performance measures must be sufficiently timely and accurate for decision-makers to use with confidence. Various groups within State Departments of Transportation (DOTs) have been collecting traffic data for generations for their own decision-making as well as for Federal Highway Administration (FHWA) programs, such as the Highway Performance Monitoring System (HPMS). Advances in traffic detection systems and the growth of Intelligent Transportation Systems (ITS) infrastructure have provided new sources and new challenges for traffic data collection. ITS infrastructure provides the ability to collect large amounts of traffic data for immediate use in operations as well as data for analytical applications through Archived Data Management Systems (ADMS). The increasing amounts and types of traffic data available from ITS enable new applications but also raise concerns about data quality.

Recent research and analysis have identified several issues regarding the quality of traffic data available from ITS for transportation operations, planning, or other functions. For example, the Advanced Traveler Information Systems (ATIS) Data Gaps Workshop in 2000 identified information accuracy, reliability, and timeliness as critical to ATIS. The key findings of the workshop, which are included in a document titled "Closing the Data Gap: Guidelines for Quality Advanced Traveler Information System (ATIS) Data", are the following:

These concerns prompted the FHWA sponsored workshops on Traffic Data Quality (TDQ) in Columbus, Ohio, and Salt Lake City, Utah in March 2003. The primary objective of the workshops was to define an action plan to address traffic data quality issues. The action plan included work items that can be executed through the U.S. Department of Transportation (DOT), stakeholder organizations (e.g., American Association of State Highway Transportation Officials [AASHTO], ITS America), and state DOTs. The action plan builds upon the findings in the white papers and inputs obtained from the regional workshops. The action plan provides a blueprint for specific actions to address traffic data quality issues. Implementation of the plan will require collaboration among both public and private partners with the FHWA and state DOTs playing leading roles. The plan identifies 10 priority action items. One of the foremost recommendations that came out of the workshops was the call for "guidelines and standards for calculating data quality measures." These guidelines and standards are expected to contain methods to calculate and report the data quality measures for various applications and levels of aggregation. In addition, the guidelines should also include:

1.2 Project Objectives and Scope

In order to move the state of the art and practice in traffic monitoring forward, these new methods and tools are needed to meet the challenge of delivering quality data. These methods will enable agencies involved in traffic data collection to formally assess and report the quality of data to the various users. The objective of this project is to develop methods and tools to enable traffic data collectors and users to determine the quality of traffic data they are providing, sharing, and using. The guidelines and standards for calculating data quality measures are intended to addresses the following key traffic data quality issues:

As such, the guidelines will include the following essential elements:

The focus of this project is to demonstrate how the concepts for defining and measuring traffic data quality can be implemented in practice. The concepts of data quality measurement are sufficiently developed and adequate data exist to allow such a demonstration to take place. Therefore, it is foreseen that most of the effort will be devoted to developing examples and case studies to apply data quality framework and documenting the framework in the form of guidelines.

1.3 Organization of Report

The remainder of the report is organized as follows:



1 Report to FHWA, Traffic Data Quality Workshop Proceedings and Action Plan, Battelle, 2003.

Executive Summary | Table of Contents | 2.0



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