The invention discloses a traffic signal lamp control method and system based on reinforcement learning, and the method comprises the steps: firstly building a signal lamp control Agent model, then building a road and road intersection model, enabling the road traffic state information to be represented as a speed, position and current signal lamp state matrix, then, on the basis of traditional Q-Learning, establishing a traffic signal lamp control algorithm based on Deep Q Network (DQN) according to the road environment information; and finally, obtaining real-time road condition information through interaction between the Agent and the environment, performing search self-learning in a behavior space, estimating Q values for executing all possible actions in the current state, and selecting the action with the larger Q to be executed by utilizing an epsilon-greedy strategy. An existing traffic signal lamp control method is improved, the waiting time of vehicles at the intersection is minimized, the effective green light time of a signal control period is maximized, the vehicles are assisted to rapidly pass through the intersection, the passing time is shortest, meanwhile, the maximum traffic flow exists at the intersection, and thus the purpose of relieving traffic jam is achieved, and adaptive control of the traffic signal lamp is realized.

    本发明公开了一种基于强化学习的交通信号灯控制方法及系统,首先建立信号灯控制Agent模型,其次建立道路及道路交叉口模型,将道路交通状态信息表示成速度、位置和当前信号灯状态矩阵,然后在传统Q‑Learning的基础上根据道路环境信息建立基于Deep Q Network(DQN)的交通信号灯控制算法;最后通过Agent与环境交互获取实时的路况信息,在行为空间进行搜索自学习,估计当前状态下执行所有可能动作的Q值,利用ε‑greedy策略选择Q较大的动作执行。本发明改进了现有的交通信号灯控制方法,最小化路口车辆的等待时间,最大化信号控制周期有效绿灯时间,助力车辆快速通过路口,有最短的通行时间,同时使路口有最大车流量,从而达到缓解交通拥堵的目的,实现交通信号灯的自适应控制。


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    Titel :

    Traffic signal lamp control method and system based on reinforcement learning


    Weitere Titelangaben:

    一种基于强化学习的交通信号灯控制方法及系统


    Beteiligte:
    LUO JUAN (Autor:in) / ZHENG YANLIU (Autor:in)

    Erscheinungsdatum :

    2021-09-10


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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