2007IRIS Research product catalog (Sapienza University of Rome)Requires access

Priority and Holding Strategies to Improve Transit Performance

Guiseppe Bellei, Konstantinos Gkoumas

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Abstract

This paper studies how speed and regularity of transit systems can be improved by means of priority and holding strategies. This objective is attained by taking into account the inherent uncertainty of transit operation, due to the random travel times and passenger arrivals at stops. The priority at intersections is assumed to be given only by green extension actuated by local sensors, with upstream stop location. The fact that delayed and crowded vehicles are less likely to get priority because of less predictable dwell times, as is the case of more complex priority strategies, is thus represented. In this perspective, a simulation model is developed and different vehicle holding and priority strategies are compared. With regard to priority different conditional strategies are also considered.

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What this paper is about

This paper studies how speed and regularity of transit systems can be improved by means of priority and holding strategies. This objective is attained by taking into account the inherent uncertainty of transit operation, due to the random travel times and passenger arrivals at stops. The priority at intersections is assumed to be given only by green extension actuated by local sensors, with upstream stop location. The fact that delayed and crowded vehicles are less likely to get priority because of less predictable dwell times, as is the case of more complex priority strategies, is thus represented. In this perspective, a simulation model is developed and different vehicle holding and priority strategies are compared. With regard to priority different conditional strategies are also considered.

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Available abstract

This paper studies how speed and regularity of transit systems can be improved by means of priority and holding strategies. This objective is attained by taking into account the inherent uncertainty of transit operation, due to the random travel times and passenger arrivals at stops. The priority at intersections is assumed to be given only by green extension actuated by local sensors, with upstream stop location. The fact that delayed and crowded vehicles are less likely to get priority because of less predictable dwell times, as is the case of more complex priority strategies, is thus represented. In this perspective, a simulation model is developed and different vehicle holding and priority strategies are compared. With regard to priority different conditional strategies are also considered.

Key concepts: Dwell time, Transit (satellite), Upstream (networking), Computer science, Transport engineering, Operations research, Engineering, Public transport

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