Motion planning in autonomous driving is a major challenge, as it needs to consider the continuity between the actions output by internal modules and the need for consistency in optimizing driving behavior. Otherwise, it may lead to overly conservative or irrational driving behavior in complex scenarios. To address these issues, we propose a hybrid model predictive motion planner (HMPC) that integrates logical decision-making and motion planning, enabling seamless planning of vehicle motion without semantic decisions or predefined trajectories while extending functionality for external decisions. Testing results reveal that HMPC surpasses the conventional hierarchical MPC motion planner, ensuring better maintenance of the desired speed and greater adaptability to external behavior decision-making modules.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Seamless Motion Planning Integrating Maneuver Decision Based on Hybrid Model Predictive Control


    Contributors:
    Tu, Chengen (author) / Li, Zhuoren (author) / Leng, Bo (author) / Xiong, Lu (author)


    Publication date :

    2023-09-24


    Size :

    2992487 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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

    Wang, Zejiang / Ahmad, Ahmad / Quirynen, Rien et al. | IEEE | 2022


    Maneuver Motion Planning Based on Virtual Target for UAVs

    Ma, Rong / Hou, Lin / Zhang, Xianglun | British Library Conference Proceedings | 2022



    Maneuver Motion Planning Based on Virtual Target for UAVs

    Ma, Rong / Hou, Lin / Zhang, Xianglun | Springer Verlag | 2021


    Emergency collision avoidance maneuver based on nonlinear model predictive control

    Chulho Choi, / Kang, Yeonsik / Seangwock Lee, | IEEE | 2012