In order to solve the problems of accuracy, comfort and robustness of driverless vehicles under parallel parking condition, a control method of path tracking based on model predictive control (MPC) is studied. The kinematics model of driverless vehicle under parking condition is established. The calculation method of minimum parking space size required for parking is proposed. The linear error model of vehicle kinematics is established. In order to make the vehicle track the desired path quickly and smoothly, an appropriate objective function is designed. In rolling optimization, the constraint conditions of velocity and front wheel steering angle are imposed on the objective function to achieve the solution in the control period, the control input constraint and control increment constraint are set. In order to ensure the stability of the path tracking process, constraint condition of velocity is set. Based on MATLAB environment, the effects of control method of path tracking based on MPC under typical parallel parking condition is studied. Two vehicle models are selected to verify effects of the path tracking control method, and good tracking results are achieved. The results show that compared with the pure pursuit control method, MPC method can make the vehicle reach the end of the planned path, the path tracking error is smaller, the change of front wheel angle is smoother, the vehicle stability and passenger comfort are better, and parking robustness is improved.


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    Titel :

    Path Tracking for Driverless Vehicle Under Parallel Parking Based on Model Predictive Control


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Yu, Leiyan (Autor:in) / Wang, Xianyu (Autor:in) / Hou, Zeyu (Autor:in)

    Kongress:

    SAE 2021 Intelligent and Connected Vehicles Symposium Part I ; 2021



    Erscheinungsdatum :

    15.12.2021




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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