The invention relates to the technical field of traffic signal control, in particular to a multi-intersection traffic signal cooperative control method, which comprises the following steps of: acquiring traffic condition information of intersections; a multi-agent model is established for the network of the N intersections through a Transform sequence model, the input of the multi-agent model is an observation sequence, the output of the multi-agent model is an action sequence, and the optimal action sequence is obtained according to the dominant decomposition theorem of the multi-agent model; wherein the observation sequence is the lane queue length of each intersection; the action sequence is a signal phase selected by each agent; and the multi-agent model executes the optimal action sequence under the observation sequence to obtain an award from environment feedback, so that the award is the maximum intersection pressure to cooperatively control traffic signals. According to the invention, the traffic signal control problem of the network-level multi-intersection can be solved, the performance of the traffic signal control algorithm is obviously improved, and the implementation complexity of the traffic signal control algorithm is reduced.
本发明涉及交通信号控制技术领域,尤其是一种多交叉口交通信号协同控制方法,包括下述步骤:获取交叉口的交通状况信息;对N个交叉口的网络通过Transformer序列模型建立多智能体模型,所述多智能体模型的输入为观测序列,且输出为动作序列,根据多智能体模型优势分解定理,获得最佳动作序列;其中,所述观测序列为各个交叉口的车道队列长度;所述动作序列为各个所述智能体选择的信号相位;所述多智能体模型在观测序列下执行最佳动作序列,以获得来自环境反馈的奖励,使所述奖励为最大的交叉口压力,以协同控制交通信号。本发明能够解决网络级多交叉口的交通信号控制问题,而且显著提高交通信号控制算法的性能并降低其实现的复杂性。
Multi-intersection traffic signal cooperative control method
一种多交叉口交通信号协同控制方法
28.11.2023
Patent
Elektronische Ressource
Chinesisch
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