In this paper, we propose a cooperative motion planning method for a group of connected and automated vehicles (CAVs) crossing a lane-free intersection without using explicit traffic signaling. This multi-vehicle motion planning task is formulated as a centralized optimal control problem. However, the solution to this optimal control problem is numerically intractable due to the high dimensionality of the collision-avoidance constraints and the nonlinearity of the vehicle kinematics. A two-stage strategy is proposed for generating online solutions: at Stage 1, the CAVs are requested to reach a standard formation before entering the intersection; at Stage 2, the vehicles cross the intersection. As the motion planning sub-problem at Stage 2 begins with a standard configuration, the optimal solution to this standard sub-problem can be computed offline in advance and applied online directly. On the other hand, the formation reconfiguration sub-problem at Stage 1 is easy to solve online. Through dividing the entire dynamic process into two periods, the difficulties in the original optimal control problem are significantly reduced so that the real-time performance is achieved.


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    Titel :

    Near-Optimal Online Motion Planning of Connected and Automated Vehicles at a Signal-Free and Lane-Free Intersection


    Beteiligte:
    Li, Bai (Autor:in) / Zhang, Youmin (Autor:in) / Zhang, Yue (Autor:in) / Jia, Ning (Autor:in) / Ge, Yuming (Autor:in)


    Erscheinungsdatum :

    2018-06-01


    Format / Umfang :

    833558 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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