The invention relates to a multi-intersection traffic signal lamp cooperative control method and device and a readable storage medium. The method comprises the following steps: acquiring traffic flow information, and inputting the traffic flow information into a traffic signal lamp control model based on a multi-agent reinforcement learning algorithm to obtain and store the state, action and reward function of each agent; an explainable influence mechanism based on an efficient link neural network is adopted, importance coefficients of input data on different traffic road networks are solved, and traffic flow hidden variables after weighted aggregation are solved; adopting a bias ReLU neural network to approach a value function and a strategy function in an act-critic reinforcement learning algorithm so as to construct a fragment linear act-critic framework; a centralized training and distributed execution method is adopted, and the actor of each agent obtains a respective strategy function through traffic flow information training; the centralized critic is trained according to the traffic flow hidden variables to obtain a joint value function, and the optimal solution of the multi-agent reinforcement learning algorithm is obtained. The efficiency and the safety of the road traffic flow can be improved.
本发明涉及多路口交通信号灯协同控制方法、设备及可读存储介质。其方法包括:获取交通流信息,输入到基于多智能体强化学习算法的交通信号灯控制模型中,以获得并存储每个智能体的状态、动作和奖励函数;采用基于高效链接神经网络的可解释影响机制,求出不同交通路网上输入数据的重要性系数,并求出加权聚合后的交通流隐变量;采用偏置ReLU神经网络逼近actor‑critic强化学习算法中的价值函数和策略函数,以构造分片线性actor‑critic的框架;采用集中式训练分布式执行的方法,每个智能体的actor通过交通流信息训练得到各自的策略函数;集中式critic根据交通流隐变量,训练得到一个联合价值函数,获得多智能体强化学习算法的最优解。本发明可提高道路交通流的效率和安全性。
Multi-intersection traffic signal lamp cooperative control method and device and readable storage medium
多路口交通信号灯协同控制方法、设备及可读存储介质
2024-09-10
Patent
Electronic Resource
Chinese
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