In the context of intelligent vehicle lane changing, a trajectory with superior performance is typically planned in accordance with the constraints of the lane change path. This allows the intelligent vehicle to execute the lane change along the preplanned trajectory. Model Predictive Control (MPC) stands out among other control methods due to its ability to incorporate a variety of constraints into the control process. This ensures that the model aligns with the actual situation, rendering the control results practically significant. Consequently, this study employs the MPC method to design the lane change path tracking controller for intelligent vehicles. The designed trajectory tracking model predictive controller is validated in a simulation environment, demonstrating effective tracking control at various vehicle speeds. Furthermore, it can execute tracking control of the vehicle’s lane change path in accordance with the planned ideal reference trajectory.


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    Titel :

    Design and simulation of intelligent vehicle lane change path tracking controller


    Beteiligte:
    Chin, Cheng Siong (Herausgeber:in) / Zhao, Wenbing (Herausgeber:in) / Cheng, Changbo (Herausgeber:in) / Zhou, Jun (Autor:in) / Zhang, Yue (Autor:in)

    Kongress:

    Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023) ; 2023 ; Wuhan, China


    Erschienen in:

    Proc. SPIE ; 12918


    Erscheinungsdatum :

    11.10.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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