The invention discloses a crossroad traffic signal lamp control method based on reinforcement learning, and the method comprises the steps: firstly enabling the passing state of a crossroad at a current moment to be expressed as a Position and Speed matrix; secondly, on the basis of a traditional reinforcement learning algorithm Deep Q-network, constructing a framework based on a spatial attentionmechanism according to the features of State, wherein a backbone network is a convolutional neural network; and then, according to a greedy strategy, one Action is randomly selected or predicted froma model to be executed. If the Action of the current moment is the same as the action of the previous moment, the green light phase time is directly executed, and the network is continuously trainedin the process; otherwise, the yellow light phase time is firstly executed, then the green light phase time is executed, and the network is continuously trained in the same process; and finally, the model is stored after all training rounds are finished, and then the effect of the model are tested and evaluated. According to the invention, an existing traffic signal lamp control method is improvedsuch that vehicles can pass through the crossroad more quickly, and traffic jam is relieved to a certain extent.

    本发明公开了一种基于强化学习的十字路口交通信号灯控制方法,首先,将当前时刻十字路口的通行状态表示成Position和Speed矩阵;其次,在传统强化学习算法Deep Q‑network的基础上根据State的特征构建基于空间注意力机制的框架,其中主干网络为卷积神经网络;然后,根据贪婪策略随机选取或者从模型预测一个Action执行。如果当前时刻的Action和前一时刻的相同,那么就直接执行绿灯相位时间,并在此过程中不断训练网络;否则,首先执行黄灯相位时间,然后,再执行绿灯相位时间,同样在此过程中同样不断地训练网络;最后,所有训练回合结束后保存模型,然后测试并评估模型效果。本发明改进了现有的交通信号灯控制方法,使得车辆能够更快的通过十字路口,一定程度上缓解了交通拥堵。


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    Title :

    Crossroad traffic signal lamp control method based on reinforcement learning


    Additional title:

    一种基于强化学习的十字路口交通信号灯控制方法


    Contributors:
    WU LIBING (author) / WANG MIN (author) / ZHANG RUI (author) / CAO SHUQIN (author)

    Publication date :

    2020-06-09


    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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