In autonomous driving, variations in tire vertical load, tire slip angle, road conditions, tire pressure and tire friction all contribute to uncertainty in tire cornering stiffness. Even the same tire may vary slightly during the manufacturing process. Therefore, the uncertainty of tire cornering stiffness has an important influence for autonomous driving path planning and control strategies. In this paper, the Chebyshev interval method is used to represent the uncertainty of tire cornering stiffness and is combined with a model predictive control algorithm to obtain the trajectory interval bands under local path planning and tracking control. The accuracy of the tire cornering stiffness model and the path tracking efficiency are verified by comparing with the path planning and control results without considering the corner stiffness uncertainties. In the local path planner that consider the uncertainty of tire cornering stiffness, an objective function that minimizes the distance between the main vehicles position and the goal position within the predicted step is added. This can effectively reduce the impact of tire lateral deflection stiffness uncertainty in path planning.


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    Titel :

    Local Path Planning and Tracking Control Considering Tire Cornering Stiffness Uncertainty


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Wang, Yanan (Autor:in) / Zhang, Yunqing (Autor:in) / Duan, Yupeng (Autor:in)

    Kongress:

    SAE WCX Digital Summit ; 2021



    Erscheinungsdatum :

    06.04.2021




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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