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APPLICATION OF TRANSIT PERFORMANCE INDICATORS

Thomas Stone, J A Austin, Richard L. Siegel, A Taylor-Harris

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Abstract

Decreasing transit ridership and increasing operating and capital costs have resulted in a situation whereby the Urban Mass Transportation Administration (UMTA) is requiring transit operators to develop comprehensive data reporting schemes. Transit operators are realizing the need for measurement of transit system productivity, efficiency, and effectiveness, in order to make decisions on where to add, modify, or delete service. The research provides an internal route-specific, performance monitoring tool, and aimed at bus transit performance. The research was devised to yield a specific product, which is a comprehensive decision framework for applying transit performance indicators. Two performance indicators were selected for use in the research, namely, passengers per bus mile and passengers per bus hour. These indicators are used primarily becuse the data are relatively easy to obtain. The application methodology is general, however, in that it can also be used for other route-specific indicators. The decision framework is based upon the statistical decision-making techniques which are used in other fields such as quality control. Two case studies were used in this framework to apply indicators to the measurement of performance of the bus transit systems of the Regional Transportation District of Denver, Colorado, and the Utah Transit Authority of the Salt Lake City, Utah region. Guidelines are given to assist transit operator programs.

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What this paper is about

Decreasing transit ridership and increasing operating and capital costs have resulted in a situation whereby the Urban Mass Transportation Administration (UMTA) is requiring transit operators to develop comprehensive data reporting schemes. Transit operators are realizing the need for measurement of transit system productivity, efficiency, and effectiveness, in order to make decisions on where to add, modify, or delete service. The research provides an internal route-specific, performance monitoring tool, and aimed at bus transit performance. The research was devised to yield a specific product, which is a comprehensive decision framework for applying transit performance indicators. Two performance indicators were selected for use in the research, namely, passengers per bus mile and passengers per bus hour. These indicators are used primarily becuse the data are relatively easy to obtain. The application methodology is general, however, in that it can also be used for other route-specific indicators. The decision framework is based upon the statistical decision-making techniques which are used in other fields such as quality control. Two case studies were used in this framework to apply indicators to the measurement of performance of the bus transit systems of the Regional Transportation District of Denver, Colorado, and the Utah Transit Authority of the Salt Lake City, Utah region. Guidelines are given to assist transit operator programs.

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Available abstract

Decreasing transit ridership and increasing operating and capital costs have resulted in a situation whereby the Urban Mass Transportation Administration (UMTA) is requiring transit operators to develop comprehensive data reporting schemes. Transit operators are realizing the need for measurement of transit system productivity, efficiency, and effectiveness, in order to make decisions on where to add, modify, or delete service. The research provides an internal route-specific, performance monitoring tool, and aimed at bus transit performance. The research was devised to yield a specific product, which is a comprehensive decision framework for applying transit performance indicators. Two performance indicators were selected for use in the research, namely, passengers per bus mile and passengers per bus hour. These indicators are used primarily becuse the data are relatively easy to obtain. The application methodology is general, however, in that it can also be used for other route-specific indicators. The decision framework is based upon the statistical decision-making techniques which are used in other fields such as quality control. Two case studies were used in this framework to apply indicators to the measurement of performance of the bus transit systems of the Regional Transportation District of Denver, Colorado, and the Utah Transit Authority of the Salt Lake City, Utah region. Guidelines are given to assist transit operator programs.

Key concepts: Transit (satellite), Transport engineering, Performance indicator, Public transport, Bus rapid transit, Capital expenditure, Level of service, Quality (philosophy)

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