Development of Dynamic Transit Signal Priority Strategy

Document Type

Journal Article

Publication Date

2009

Subject Area

operations - traffic, infrastructure - bus/tram priority, infrastructure - bus/tram priority, infrastructure - traffic signals, mode - bus, mode - rail, mode - tram/light rail, mode - mass transit

Keywords

VISSIM (Computer model), Travel time, Transit, Traffic signal priority systems, Traffic signal preemption, Traffic delay, Signalized intersections, Signalised intersections, Real time control, Public transit, Preemption (Traffic signals), Mass transit, Local transit, Light rail transit, Journey time, Intracity bus transportation, Case studies, Bus transit, Bus priority, Algorithms

Abstract

Transit signal priority (TSP) is a popular strategy used to enhance the performance of transit systems by modifying the signal control logic to give transit vehicles priority at signalized intersections. Conventional TSP strategies used in most cities have been shown to offer significant benefits by reducing delay of transit vehicles. However, concerns about shortcomings of conventional TSP strategies have limited their application. The main concern is a potential negative impact on cross street traffic. Another concern is the static nature of conventional TSP strategies and the lack of responsiveness to real-time traffic and transit conditions. A dynamic TSP control system has been developed that can provide signal priority in response to real-time traffic and transit conditions. The dynamic TSP system consists of three main components: a virtual detection system, a dynamic arrival prediction model, and a dynamic TSP algorithm. Two case studies are presented to test and compare the dynamic and the conventional TSP systems. A hypothetical intersection is simulated in the first case study, and a proposed light rail transit line is simulated in the second. For both case studies, a virtual detection system was developed in VISSIM, along with a linear travel time arrival prediction model. Finally, a dynamic TSP algorithm was developed to determine what TSP strategy to use and when to apply it. The results show that the dynamic TSP system reduced the total delay of transit vehicles and outperformed the conventional TSP system for reducing transit trip travel time.

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