It is necessary to generate a collision-free path for lane changing when automated vehicles encounter obstacles in front and cannot continue to drive in the original lane. In this paper, we propose an effective path planning and tracking method based on quintic Bézier curve and pure pursuit for automated vehicles with low velocity. Firstly, a novel method for selecting the control points of quintic Bézier curve can be applied in straights and curves is proposed. Then, the path-planning problem is converted to an optimization problem, considering the curvature, the swing angle and the collision with obstacles. Finally, a path tracking controller with high tracking accuracy based on pure pursuit is designed, which considers the curvature of path and the lateral preview deviation. Results of simulation and on-vehicle experiment show that the proposed method can generate reasonable path for lane changing in both straights and curves. Comparing to traditional pure pursuit, the accuracy of tracking path is promoted. The research results demonstrate the validity of proposed method and enjoy great application value in engineering.


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    Titel :

    Lane Change Control of Automated Vehicle Based on Adaptive Preview Distance


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Huang, Bin (Autor:in) / Zhou, Jia-Qiang (Autor:in) / Fu, Wen-Qi (Autor:in)

    Kongress:

    SAE 2022 Intelligent and Connected Vehicles Symposium ; 2022



    Erscheinungsdatum :

    22.12.2022




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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