In recent years significant progress has been made in optimization-based planning and control for automated vehicle operation. For heavy-duty vehicles, the research focus has been on platooning and control of articulated vehicles especially when cruising on the highway. This paper proposes an integrated system using a motion planning algorithm and a real-time reference tracking controller, tailored to the task of automated tractor-trailer hitching which is a critical maneuver in heavy-duty vehicle operations, due to requiring a very high precision. The motion planner is based on a bi-directional A-search guided tree algorithm and the tracking controller is im-plemented using nonlinear model predictive control. To validate the proposed approach, we present results from hardware-in-the-loop simulations on a dSPACE Scalexio real-time computing unit and extensive Monte Carlo closed-loop simulations.


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    Titel :

    Motion Planning and Model Predictive Control for Automated Tractor-Trailer Hitching Maneuver


    Beteiligte:
    Wang, Zejiang (Autor:in) / Ahmad, Ahmad (Autor:in) / Quirynen, Rien (Autor:in) / Wang, Yebin (Autor:in) / Bhagat, Akshay (Autor:in) / Zeino, Eyad (Autor:in) / Zushi, Yuji (Autor:in) / Di Cairano, Stefano (Autor:in)


    Erscheinungsdatum :

    2022-08-23


    Format / Umfang :

    2728722 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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