In order to improve the road traveling efficiency and vehicle driving safety, a lane selection artificial potential field method is proposed based on the dynamic topology of the vehicle cluster model with Internet of Vehicles. The real-time decisions of lane changing for collision avoidance are made by the reformed lane repulsion of artificial potential field. Then, a lane-changing trajectory is planned using 2-segment 3-order Bezier curves. Meanwhile the safety control points of the main lane and the safe distances of the target lane are proposed as the safe constraints for lane-changing process. Finally, based on the MATLAB platform, the simulation is performed for validation under the typical conditions of different obstacles under the high-speed background. The results show that the lane selection artificial potential field method can make the real-time lane-changing decision effectively, and the lane-changing trajectory planning under the set safe constraints can effectively avoid the occurrence of vehicle collision accidents.


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    Titel :

    Research on vehicle lane-changing obstacle avoidance for Internet of Vehicles


    Beteiligte:
    Kong, Zhengmin (Herausgeber:in) / Saeed, Nasir (Herausgeber:in) / Cong, Hao (Autor:in) / Li, Xueming (Autor:in) / Huang, Cao (Autor:in)

    Kongress:

    International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2023) ; 2023 ; Changsha, China


    Erschienen in:

    Proc. SPIE ; 12641


    Erscheinungsdatum :

    12.05.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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