The invention provides an urban traffic signal reinforcement learning control method considering phase switching and duration adjustment, and the method comprises the steps: taking a traffic signal control system of an urban road intersection as a deep reinforcement learning agent, and collecting the traffic flow information of a controlled intersection in real time through a sensor; each time at the end moment of the current phase of the traffic signal, the intelligent agent calculates a state and an award based on the collected traffic flow information, trains a strategy network containing two deep neural sub-networks based on a DQN deep reinforcement learning framework, and then calculates a new action based on the state and the strategy network, so as to obtain a new action; adjusting the traffic signal to a new phase or prolonging the current phase duration; and after multiple times of training, an optimized traffic signal control strategy network is obtained. The traffic signal phase and the phase duration are dynamically adjusted based on the real-time traffic flow data and deep reinforcement learning, optimization of controlled intersection traffic flow scheduling is facilitated, and the method is suitable for different intersections and traffic flow change scenes and has wide application prospects.

    本发明提出一种考虑相位切换与时长调整的城市交通信号强化学习控制方法,该方法以城市道路交叉口的交通信号控制系统作为深度强化学习的智能体,通过传感器实时采集受控路口的车流信息;每次在交通信号当前相位的结束时刻,智能体基于采集的车流信息计算状态与奖励,并基于DQN深度强化学习框架,对其中包含两个深度神经子网络的策略网络进行训练,之后基于状态和策略网络计算新动作,将交通信号调整新的相位或者延长当前的相位时长;经过多次训练后,得到优化的交通信号控制策略网络。本发明基于实时车流数据与深度强化学习动态调整交通信号相位和相位时长,有助于优化受控路口车流调度,适用于不同交叉口和车流量变化场景,具有广泛应用前景。


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Urban traffic signal reinforcement learning control method considering phase switching and duration adjustment


    Weitere Titelangaben:

    一种考虑相位切换与时长调整的城市交通信号强化学习控制方法


    Beteiligte:
    XIE MENGWEI (Autor:in) / CHEN GUANG (Autor:in) / JIN RONG (Autor:in)

    Erscheinungsdatum :

    13.05.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

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



    Urban traffic signal control using reinforcement learning agents

    Balaji, P.G. / German, X. / Srinivasan, D. | IET | 2010


    Multi-agent reinforcement learning traffic signal cooperative control method considering intersection heterogeneity

    BIE YIMING / JI YUTING / JI JINHUA et al. | Europäisches Patentamt | 2024

    Freier Zugriff



    Traffic Signal Switching Strategy Based on Reinforcement Learning Algorithm

    Hu, Linjian / Xu, Shibo / Li, Xiaoyang et al. | British Library Conference Proceedings | 2022