The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem.


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    Titel :

    Parking Planning with Genetic Algorithm for Multiple Autonomous Vehicles


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Luo, Chagen (Autor:in) / Zeng, Dequan (Autor:in) / Xu, Feng (Autor:in) / Zhang, Peizhi (Autor:in) / Hu, Yiming (Autor:in) / Deng, Zhenwen (Autor:in) / Fu, Zhiqiang (Autor:in) / Li, Zhuoren (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2022



    Erscheinungsdatum :

    2022-03-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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