The invention discloses an urban traffic optimization and planning system based on reinforcement learning, and relates to the technical field of computer information, and the system comprises a traffic data acquisition unit, a reinforcement learning processing unit and a traffic planning unit. The traffic data acquisition unit is used for regarding target urban traffic as a network and regarding each intersection as a node, and constructing a nonlinear traffic flow dynamic model to update a multi-dimensional tensor at each time step; the reinforcement learning processing unit is used for taking a signal timing matrix of a signal lamp of a road section between every two nodes of target urban traffic as a state space and calculating a corresponding action space when a target reward function is a maximum value; and the traffic planning unit is used for finishing the traffic planning of the target city according to the action space of each road section. According to the method, the global optimization capability, the multi-objective optimization capability, the adaptive learning capability, the data processing capability, the safety and the interpretability of traffic signal control are remarkably improved.
本发明公开了基于强化学习的城市交通优化与规划系统,涉及计算机信息技术领域,所述系统包括:交通数据获取单元、强化学习处理单元和交通规划单元;所述交通数据获取单元,用于将目标城市交通视为一个网络,每个路口视为一个节点,构建非线性交通流动力学模型以在每个时间步更新多维张量;所述强化学习处理单元,用于将目标城市交通在每两个节点之间的路段的信号灯的信号配时矩阵作为状态空间,计算出在目标奖励函数为最大值时的对应的动作空间;所述交通规划单元,用于根据每个路段的动作空间,完成目标城市交通的规划。本发明显著提升了交通信号控制的全局优化能力、多目标优化能力、自适应学习能力、数据处理能力以及安全性和可解释性。
Urban traffic optimization and planning system based on reinforcement learning
基于强化学习的城市交通优化与规划系统
2024-12-13
Patent
Electronic Resource
Chinese
IPC: | G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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