In recent years, rapid technological breakthroughs in infrastructure-to-vehicle, vehicle-to-vehicle, and vehicle-to-infrastructure wireless communications have created the possibility of new concepts for traffic signal control. The green light optimized speed advisory (GLOSA) approach uses traffic signal control information and the current position of a vehicle to recommend an appropriate speed for each vehicle, reducing the number of stops at traffic signals. Previous research mainly focused on the impact of GLOSA on the performance of movements on major streets. The purpose of this paper is to examine the effects of GLOSA on delay, capacity, and surrogate safety measures for vehicles that arrive from unsignalized side driveways and access roads. A highly calibrated and validated Vissim simulation model of a five-intersection segment of 3500 South, an urban corridor in Salt Lake City, Utah, was used as a test environment. Scenarios of various traffic loads and GLOSA activations have been defined and simulated. Outputs from Vissim were used to measure the impact of GLOSA. Vehicular trajectory files were postprocessed in the FHWA Surrogate Safety Assessment Model to analyze vehicular conflict data and thereby evaluate the traffic safety effects of GLOSA. The findings show that GLOSA often significantly affects delay of the side-street traffic. However, in general, GLOSA has only a minor impact on the number of conflicts. Regarding the impact of type of traffic control on GLOSA’s operations, the findings show that the fixed-time signals work better than actuated–coordinated signals, and road geometry and proximity of the signalized intersections affect the impact of GLOSA on the side-street traffic.


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    Titel :

    Impact of Green Light Optimized Speed Advisory on Unsignalized Side-Street Traffic


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.2016




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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