The invention discloses a collaborative automatic driving vehicle scheduling method based on a deep reinforcement learning framework. The method comprises the following steps: firstly, designing a reward function formed by combining a system-level speed reward and a time headway punishment; then, a joint state space based on a reinforcement learning framework is designed, and the joint state space comprises information such as relative speed and relative distance between a front vehicle/rear vehicle of the same lane, a front vehicle/rear vehicle of a left adjacent lane and a front vehicle/rear vehicle of a right adjacent lane; thirdly, combining the acceleration output vector and the lane changing action of the automatic driving vehicle, and designing a joint action space for reinforcement learning; finally, the designed deep reinforcement learning framework is fully trained, stable vehicle speed, lane changing and other control information can be output, and cooperative intelligent control over the automatic driving vehicle is achieved. According to the method provided by the invention, the average passing speed of the vehicle under the condition of mixed driving of the manual driving vehicle and the automatic driving vehicle in the continuous confluence and divergence bottleneck traffic scene can be improved, and the collision danger frequency of the vehicle is reduced.

    本发明公开一种基于深度强化学习框架的协作式自动驾驶车辆调度方法。首先,设计系统级速度奖励和车头时距惩罚组合而成的奖励函数;然后,设计出基于强化学习框架的联合状态空间,该联合状态空间包括同车道前车/后车、左侧相邻车道前车/后车、右侧相邻车道前车/后车之间相对速度和相对距离等信息;接着,将自动驾驶车辆的加速度输出矢量和变道动作进行组合,设计出强化学习的联合动作空间;最后,对设计的深度强化学习框架进行充分训练,可输出稳定的车速和变道等控制信息,实现自动驾驶车辆的协作智能控制。本发明所提方法,能够提高连续合分流瓶颈交通场景下人工驾驶和自动驾驶车辆混行情况下车辆的平均通行速度,并减少车辆的碰撞危险次数。


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    Title :

    Automatic driving vehicle scheduling method under continuous confluence and divergence bottleneck traffic scene


    Additional title:

    一种连续合分流瓶颈交通场景下自动驾驶车辆调度方法


    Contributors:
    TAN GUOPING (author) / TANG BAIXIONG (author) / SHAO XIAOFENG (author) / CHEN HAO (author) / YUAN HUI (author) / WANG XU (author) / LEE HEE-CHUL (author)

    Publication date :

    2025-01-03


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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