GPS-based transit signal priority (TSP) is a new type of transit preferential tool being considered in many North American cities. With GPS detection and advanced communications, GPS-based TSP provides flexible and conditional signal priority to transit vehicles. This is a relatively new system with limited field implementations and evaluations. The research in this study used microscopic simulation, to create a set of TSP scenarios for a 3-mi bus corridor and evaluated the influences of GPS-based TSP on transit and traffic operations. The simulation network was the 3300 South corridor, including side streets, in Salt Lake County, Utah. A proposal was evaluated to upgrade the Utah Transit Authority Bus Route 33 operating along the corridor into a bus rapid transit (BRT) line running in mixed traffic. Eight simulation scenarios were created to cover ( a) current field conditions, ( b) regular bus with traditional TSP implementation, ( c) regular bus with GPS-based TSP, ( d) BRT implementation with no TSP, ( e) BRT with traditional TSP implementation, ( f) BRT with GPS-based TSP, ( g) BRT with conditional TSP, and ( h) BRT with multiconditional TSP implementation. The evaluation included transit and nontransit operations, and the impacts on side-street traffic. The results show that GPS-based TSP performed as effectively as did traditional TSP. Conditional and multi-conditional TSP strategies showed benefits in providing the transit system considerable delay reduction (13% and 3%, respectively) and travel time savings (7% and 3%, respectively) while having the smallest impacts on side-street traffic (3% and 1% increase in delay, respectively) compared with other TSP strategies.


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    Title :

    Evaluation of GPS-Based Transit Signal Priority for Mixed-Traffic Bus Rapid Transit


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2016-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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