Autonomous vehicle safety active obstacle avoidance can reduce traffic accidents and improve vehicle comfort and safety, this paper first improves the traditional artificial potential field method by designing three different obstacle potential field models for road boundaries, crossable obstacles, and no crossable obstacles and introducing the effect of speed on vehicle obstacle avoidance. Secondly, based on the vehicle dynamics model, the improved artificial potential field model is used as a function of the obstacle avoidance function of the model prediction controller. Then the PID controller is used as the internal control loop to design a double-loop closed-loop structure. Finally, the feasibility and effectiveness of the designed controller are verified by joint CarSim/Simulink simulation. The research results show that the APF-PID-MPC controller designed in this paper can improve the vehicle’s safety, stability, and comfort.


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    Titel :

    Research on Active Obstacle Avoidance Based on Model Predictive Control of Unmanned Vehicles


    Beteiligte:
    Yang, Mingxing (Autor:in) / Niu, Longjiang (Autor:in)


    Erscheinungsdatum :

    21.07.2023


    Format / Umfang :

    963252 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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