1996Unpublished venueRequires access

RAIL TRANSIT CAPACITY

Tom Parkinson, Ian Fisher

Open publisher page 15 citations

Abstract

This study investigated and quantified the variables that affect the maximum passenger carrying capacity of rail transit in four categories--rail rapid transit (heavy rail), light rail transit, commuter rail, and automated guideway transit (AGT)--in North America. A comprehensive survey of existing literature on rail transit capacity was conducted. A survey of rail transit operators in Canada, Mexico and the United States determined the capacity and capacity constraints of each system. Appropriate data were collected from these agencies and in field visits. Quantitative analysis, narration and calibration to real life result in procedures for estimating rail transit capacity under a wide variety of conditions, including realistic operating margins. The procedures are divided into two sets, a basic simple method of estimation, and a comprehensive method that includes more variables. The results show that the maximum capacity on a double track urban rail transit line can be obtained with a moving-block signaling system which has the potential for a 30% increase in train throughput compared to conventional signaling. The single most important factor in maximizing capacity is to control and reduce dwell time through station and car design.

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What this paper is about

This study investigated and quantified the variables that affect the maximum passenger carrying capacity of rail transit in four categories--rail rapid transit (heavy rail), light rail transit, commuter rail, and automated guideway transit (AGT)--in North America. A comprehensive survey of existing literature on rail transit capacity was conducted. A survey of rail transit operators in Canada, Mexico and the United States determined the capacity and capacity constraints of each system. Appropriate data were collected from these agencies and in field visits. Quantitative analysis, narration and calibration to real life result in procedures for estimating rail transit capacity under a wide variety of conditions, including realistic operating margins. The procedures are divided into two sets, a basic simple method of estimation, and a comprehensive method that includes more variables. The results show that the maximum capacity on a double track urban rail transit line can be obtained with a moving-block signaling system which has the potential for a 30% increase in train throughput compared to conventional signaling. The single most important factor in maximizing capacity is to control and reduce dwell time through station and car design.

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Available abstract

This study investigated and quantified the variables that affect the maximum passenger carrying capacity of rail transit in four categories--rail rapid transit (heavy rail), light rail transit, commuter rail, and automated guideway transit (AGT)--in North America. A comprehensive survey of existing literature on rail transit capacity was conducted. A survey of rail transit operators in Canada, Mexico and the United States determined the capacity and capacity constraints of each system. Appropriate data were collected from these agencies and in field visits. Quantitative analysis, narration and calibration to real life result in procedures for estimating rail transit capacity under a wide variety of conditions, including realistic operating margins. The procedures are divided into two sets, a basic simple method of estimation, and a comprehensive method that includes more variables. The results show that the maximum capacity on a double track urban rail transit line can be obtained with a moving-block signaling system which has the potential for a 30% increase in train throughput compared to conventional signaling. The single most important factor in maximizing capacity is to control and reduce dwell time through station and car design.

Key concepts: Rail transit, Transit (satellite), Transport engineering, Urban rail transit, Track (disk drive), Dwell time, Public transport, Computer science

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