In order to make the intelligent vehicle run safely and improve the applicability of local path planning algorithm in intelligent vehicle, the paper presents a local path planning method for intelligent vehicles. Firstly, establish vehicle model of Ackerman steering. In addition, the minimum turning radius constraint is added to the speed screening mechanism based on the traditional dynamic window approach. Then, in order to avoid excessive changes in the driving speed of intelligent vehicles, the curvature retention evaluation index is added to the evaluation function. The simulation results show that the improved algorithm meets the requirements of intelligent vehicle dynamic obstacle avoidance and can plan a safe and reasonable path.


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    Titel :

    Research on local path planning of intelligent vehicle based on improved dynamic window approach


    Beteiligte:
    Hang, Peng (Autor:in) / Yan, Yan (Autor:in) / Fu, Xianlan (Autor:in) / Chen, Haishan (Autor:in) / Liu, Yingjie (Autor:in)

    Kongress:

    Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) ; 2022 ; Wuhan,China


    Erschienen in:

    Proc. SPIE ; 12610


    Erscheinungsdatum :

    28.04.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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