The predictive motion prediction of surrounding vehicles is an essential precondition for precise collision risk assessment and path planning. In this paper, we propose a motion planning framework for autonomous driving vehicle considering surrounding vehicle motion prediction in highway scenarios. Firstly, Interactive multi-model is put forward to predict lateral positions of the surrounding vehicles. Then, with the predicted trajectory, optimization-based motion planning methods is utilized to process risk assessment model and reference path tracking error. In terms of control module, apply the MPC method for local trajectory tracking with vehicle's dynamic constraints. Finally, the simulation results in highway scenarios verify the capability of proposed framework.


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    Titel :

    Motion Planning Framework for Autonomous Vehicle with Surrounding Vehicle Motion Prediction in Highway Scenarios


    Beteiligte:
    Wang, Lei (Autor:in) / Yin, Guodong (Autor:in) / Xu, Liwei (Autor:in) / Dong, Fengwei (Autor:in) / Xu, Mingcheng (Autor:in) / He, Zh angcheng (Autor:in)


    Erscheinungsdatum :

    28.10.2022


    Format / Umfang :

    4837016 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch