This project aims at development of a more effective approach to transit signal priority (TSP) through integration of real-time adaptive signal control technology with dedicated short range communication (DSRC)-based detection of buses and communication of status information. The project focuses specifically on extending the Surtrac adaptive signal control system (in particular, the core intersection scheduling procedure) to achieve TSP objectives while at the same time minimizing the disruptive effects to overall traffic flow efficiency. Recent work with Surtrac has produced an intersection scheduling procedure that inputs weights reflective of the relative priority of vehicles and pedestrians, and uses these weights to generate signal timing plans that minimize the cumulative weighted delay of currently perceived incoming traffic flows. Taking this procedure as a starting point, the project first investigates an extension that factors knowledge of bus stop locations and expected dwell times into Surtrac’s aggregate representation of traffic inflows to more accurately reflect bus arrival times at the intersection (as well as the arrival times of passenger vehicles that are likely to be blocked during dwell time at the bus stop). In Phase 2, the project considers the added benefit of exploiting real-time bus status information, including such factors as bus schedule status (ahead or behind), bus occupancy, and bus door status (open or closed). In each of these two phases of the project, technology results will be evaluated first in simulation and then in the field. Field tests during both research phases will be carried out on the 24-intersection, DSRC-equipped test bed network that comprises the western end of the East Liberty Surtrac deployment.


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    Title :

    Integrating Transit Signal Priority with Adaptive Signal Control in a Connected Vehicle Environment


    Contributors:
    S. F. Smith (author) / I. Isukapati (author) / E. Bronstein (author) / C. Igoe (author)

    Publication date :

    2018


    Size :

    37 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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