The invention discloses a multi-vehicle collaborative decision-making method and device for a mixed traffic flow intersection, a medium and a product, and relates to the technical field of multi-vehicle collaborative decision-making, and the method comprises the steps: constructing a sequential game-based value decomposition multi-agent deep reinforcement learning model of an action filter fusing the interaction between intelligent vehicles and the interaction between the intelligent vehicles and manned vehicles; training a sequential game-based value decomposition multi-agent deep reinforcement learning model; and inputting the global state information of the intelligent vehicle to be subjected to collaborative decision making in the mixed traffic flow and the current collaborative decision making information into the trained sequential game-based value decomposition multi-agent deep reinforcement learning model, and determining the collaborative decision making information of the intelligent vehicle at the next moment. The sequential game-based action filter is added to the value decomposition multi-agent deep reinforcement learning model, so that the sample efficiency and the convergence speed of the algorithm are improved, the intersection passing collision risk of the intelligent network connection vehicle in the mixed traffic flow environment is reduced, and the traffic flow efficiency of the intersection is improved.
本发明公开一种混合交通流路口的多车协同决策方法、装置、介质及产品,涉及多车协同决策技术领域,方法包括:构建了融合智能车之间及智能车与有人驾驶车辆交互的基于序贯博弈的动作滤波器的值分解多智能体深度强化学习模型;训练基于序贯博弈的值分解多智能体深度强化学习模型;将混合交通流中待协同决策的智能车辆的全局状态信息与当前协同决策信息输入至训练好的基于序贯博弈的值分解多智能体深度强化学习模型,确定智能车辆的下一时刻的协同决策信息。通过向值分解多智能体深度强化学习模型中增加基于序贯博弈的动作滤波器,提高了算法的样本效率及收敛速度,降低了智能网联车在混合交通流环境下路口通行碰撞风险,提高路口的交通流效率。
Multi-vehicle collaborative decision-making method and device for mixed traffic flow intersection, medium and product
混合交通流路口的多车协同决策方法、装置、介质及产品
2024-11-08
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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