The invention discloses a signal lamp control method based on road network division and boundary flow control, and the method comprises the steps of dividing an urban global traffic road network into sub road network clusters through employing a road network division method based on the maximum cooperation degree, taking each intersection of the sub road networks as an agent, designing a multi-agent reinforcement learning method based on a deep neural network, and learning and generating an optimal cooperative control strategy of the signal lamps in the sub road networks through continuous interaction between the agents in the sub networks and the surrounding traffic environment in an action execution process. And meanwhile, by calibrating a sub road network macroscopic fundamental diagram model, flow control is performed on boundary road sections and intersections of the sub road networks, and the traffic operation state and the traffic efficiency of the sub road networks are further optimized. Compared with a traditional traffic signal lamp control method, the method has the advantages that the global road network is divided from the global perspective, efficient control of the urban signal lamps are achieved through cooperative control over the multiple signal lamps in the sub road networks and flow control over the sub network boundary, and the method has great significance in relieving urban traffic congestion.
本发明公开了一种基于路网划分和边界流量控制的信号灯管控方法,本方法先采用基于最大协同度的路网划分方法将城市全域交通路网划分为子路网簇,并将子路网的每个路口视为一个智能体,设计基于深度神经网络的多智能体强化学习方法,通过子网内智能体执行动作过程中与周围交通环境不断交互来学习生成子路网内信号灯最优协同控制策略。同时通过标定子路网宏观基本图模型,对子路网边界路段及路口进行流量控制,进一步优化子路网交通运行状态和通行效率。本发明相对于传统的交通信号灯控制方法,从全局角度对全域路网进行划分,通过对子路网内多信号灯的协同控制和子网边界的流量控制,实现城市信号灯的高效管控,对缓解城市交通拥堵具有重大意义。
Signal lamp control method based on road network division and boundary flow control
一种基于路网划分和边界流量控制的信号灯管控方法
2022-02-11
Patent
Elektronische Ressource
Chinesisch
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