This study presents an optimal control strategy for connected and automated vehicles (CAVs) at unsignalized intersections. A control framework with task-decomposition is designed for the near-intersection area. Firstly, the continuous traffic flow is discretized with a proposed intersection area-division scheme. Then, vehicles in different lanes are regrouped based on longitudinal positions to establish multivehicle cooperative optimal control problems of limited vehicle number. The expected optimal trajectory in the merging zone is obtained through offline simulation, which simplifies the constraints of the optimal control problem and improves the real-time performance of the online trajectory solving. Finally, an ideal capacity model is proposed based on the transit time window of vehicle, so that the capacity of a single lane is increased to 2400veh/h. The simulation results demonstrate that the proposed strategy ensures the driving safety at the unsignalized intersection, and this strategy efficiently reduces planning time for vehicle trajectories.


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    Titel :

    Optimal Control of Connected and Automated Vehicles at Unsignalized Intersections: Discrete and Regroup


    Beteiligte:
    Qian, Lijun (Autor:in) / Chen, Chen (Autor:in) / Wu, Bing (Autor:in) / Xuan, Liang (Autor:in) / Wang, Tianxiang (Autor:in)


    Erscheinungsdatum :

    01.06.2020


    Format / Umfang :

    2576654 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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