Autonomous driving of multi-lane vehicle platoons have attracted significant attention in recent years due to their potential to enhance the traffic-carrying capacity of the roads and produce better safety for drivers and passengers. This paper proposes a distributed motion planning algorithm to ensure safe overtaking of autonomous vehicles in a dynamic environment using the Artificial Potential Field method. Unlike the conventional overtaking techniques, autonomous driving strategies can be used to implement safe overtaking via formation control of unmanned vehicles in a complex vehicle platoon in the presence of human-operated vehicles. Firstly, we formulate the overtaking problem of a group of autonomous vehicles into a multi-target tracking problem, where the targets are dynamic. To model a multi-vehicle system consisting of both autonomous and human-operated vehicles, we introduce the notion of velocity difference potential field and acceleration difference potential field. We then analyze the stability of the multi-lane vehicle platoon and propose an optimization-based algorithm for solving the overtaking problem by placing a dynamic target in the traditional artificial potential field. A simulation case study has been performed to verify the feasibility and effectiveness of the proposed distributed motion control strategy for safe overtaking in a multi-lane vehicle platoon.


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    Titel :

    Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field


    Beteiligte:
    Xie, Songtao (Autor:in) / Hu, Junyan (Autor:in) / Bhowmick, Parijat (Autor:in) / Ding, Zhengtao (Autor:in) / Arvin, Farshad (Autor:in)

    Erscheinungsdatum :

    2022-11-01


    Anmerkungen:

    IEEE Transactions on Intelligent Transportation Systems , 23 (11) pp. 21531-21547. (2022)


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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