Close interaction between vehicles is prone to traffic conflicts and fluctuations at intersections. We propose an autonomous intersection traffic management scheme based on segmented dynamic programming. The main purpose of the study was to make sure that autonomous vehicles can pass through intersections without traffic lights safely and smoothly. A mixed-integer nonlinear programming is formulated to model the microscopic behavior of autonomous vehicles and ensure the collision-free among them. In a given period of time, the maximum average speed of vehicles passing through the intersection is the optimization objective of the model. Our experimental results confirm that the proposed model can effectively maximize the average vehicle speed and completely avoid accidents at intersections.


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    Titel :

    Trajectory Planning for Autonomous Vehicles at Autonomous Intersection


    Beteiligte:
    Chen, Jing (Autor:in) / Mu, Chen (Autor:in) / Zhao, Lu (Autor:in)

    Kongress:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Erschienen in:

    CICTP 2020 ; 332-342


    Erscheinungsdatum :

    12.08.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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