The invention provides a public transport priority traffic signal cooperative control method based on multi-agent deep reinforcement learning, and aims to optimize urban traffic flow and improve the traffic efficiency of public transport vehicles. The method comprises the following steps: firstly, collecting traffic state data in real time through an urban traffic monitoring system, including vehicle flow, traffic congestion degree, traffic signal lamp state and other information; then, inputting the data into a pre-trained deep Q network model; the model is trained by using historical traffic state data, and can predict the influence of different traffic signal lamp control strategies on the traffic efficiency of the public transport vehicles. According to a model prediction result, the system automatically adjusts a control strategy of the traffic signal lamp, and the smoothness and on-time arrival of the public transport vehicle are preferentially guaranteed. On the basis, the model can be continuously learned and adjusted according to real-time data so as to adapt to changes of traffic conditions.

    本发明提出了一种基于多智能体深度强化学习的公交优先交通信号协同控制方法,旨在优化城市交通流并提高公交车辆的通行效率。该方法包括以下步骤:首先,通过城市交通监控系统实时收集交通状态数据,包括车辆流量、交通拥堵程度和交通信号灯状态等信息。然后,将这些数据输入到预先训练好的深度Q网络模型中。该模型使用历史交通状态数据训练,能够预测不同交通信号灯控制策略对公交车辆通行效率的影响。根据模型预测的结果,系统自动调整交通信号灯的控制策略,优先保障公交车辆的畅通和准点到站。在此基础上,模型还能够根据实时数据不断学习和调整,以适应交通状况的变化。


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    Title :

    Bus priority traffic signal cooperative control method based on multi-agent deep reinforcement learning


    Additional title:

    一种基于多智能体深度强化学习的公交优先交通信号协同控制方法


    Contributors:
    WANG CONGYU (author) / WANG CHONG (author) / LI LEQI (author) / LIANG ZHAN (author) / ZHANG YUNYI (author)

    Publication date :

    2024-03-22


    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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen




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