The invention discloses a multi-vehicle cooperative trajectory planning parking optimization method, which utilizes an adaptive particle swarm algorithm and a sequential quadratic programming algorithm to iteratively solve a single vehicle trajectory model, can improve the robustness and convergence capability of the model, and improves the parking efficiency and energy efficiency at the same time. In a parking optimization model, through an optimization strategy combining local trajectory optimization and global trajectory optimization, rapid cooperative trajectory planning of multiple vehicles is realized in a non-convex and crowded environment, and the method has high efficiency, robustness and optimality. The parking track can be more accurately and quickly calculated in the narrow and compact parking space, static and dynamic obstacles are more flexibly avoided, the parking efficiency is fully improved, the energy loss is reduced, and the user experience is improved. The method has a wide prospect in the field of unmanned driving.

    本发明公开了一种多车协同轨迹规划泊车优化方法,利用自适应粒子群算法和顺序二次规划算法迭代求解单车轨迹模型,能够提高模型的鲁棒性和收敛能力,同时提高泊车效率和能量效率;在泊车优化模型中,通过局部轨迹优化和全局轨迹优化相结合的优化策略,在非凸且拥挤的环境中实现多车辆的快速协作的轨迹规划,具有高效性、鲁棒性和最优性。本发明能够在狭小紧密的停车空间内更精准快速的计算出泊车轨迹,更灵活的避开静态及动态的障碍物,充分提高了泊车的效率,减少了能量的损耗,提升了用户的体验。本发明在无人驾驶领域有着广阔前景。


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    Title :

    Multi-vehicle cooperative trajectory planning parking optimization method


    Additional title:

    多车协同轨迹规划泊车优化方法


    Contributors:
    CHEN LANPING (author) / CHEN CHENGYUAN (author) / XU LEI (author) / ZHU YUE (author) / YANG FAN (author) / ZHU FUCHEN (author) / WU JINXUAN (author)

    Publication date :

    2024-10-18


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion





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