In order to solve the safety problems caused by the vehicles collision on the highway, an automatic controller is proposed based on the artificial potential field (APF) method and the model predictive control (MPC) theory to keep the automatic driving vehicles collision-free. Firstly, in the path planning, the road potential field is constructed to satisfy the constraints of vehicle safe driving based on the driving characteristics of vehicles and road boundary conditions. Secondly, according to the shape of the obstacle vehicle in the study, the obstacle vehicle potential field is established. Finally, in order to ensure that the vehicle can drive along the planned path in a stable and safe manner, this paper combines the MPC and vehicle dynamics to design the path tracking module. Then the designed automatic controller is verified on the Carsim-Simulink joint simulation platform based on the obstacle vehicle uniform speed and acceleration test scenarios. The results show that the automatic controller enables road vehicles to safely avoid dynamic obstacle vehicles by updating design parameters in real time to adapt to the changing environment while satisfying environmental constraints and vehicle stability.


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    Titel :

    Dynamic Obstacle Avoidance Method for Road Vehicles Via Improved Artificial Potential Field


    Beteiligte:
    Xu, Mingyang (Autor:in) / Xu, Chen (Autor:in) / Qi, Gengxin (Autor:in) / Yue, Ming (Autor:in) / Zhao, Xudong (Autor:in)


    Erscheinungsdatum :

    27.10.2023


    Format / Umfang :

    2874879 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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