Connected vehicle technology holds great promises for next generation of traffic signal control. This paper proposes a novel mixed-integer linear programming (MILP) model to optimally coordinate traffic signals at the network level under connected vehicles environment. We leveraged the combinatorial Benders decomposition method to solve this large-scaled MILP model more efficiently than the SCIP solver. Numerical experiments show that our approach can significantly improve network traffic operations compared to a benchmark signal plan in terms of vehicle delay, travel time and throughput.


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    Titel :

    Network-wide Traffic Signal Optimization under Connected Vehicles Environment


    Beteiligte:
    Hu, Liang (Autor:in) / Wang, Lanjun (Autor:in) / Zhou, Zirui (Autor:in) / Sheng, Zhenli (Autor:in) / Zhang, Yong (Autor:in)


    Erscheinungsdatum :

    2021-09-19


    Format / Umfang :

    533753 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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