Expressway traffic efficiency improving method based on reinforced learning variable speed-limit control
A fast road and reinforcement learning technology, which is applied to the arrangement of variable traffic instructions, traffic control systems, traffic control systems of road vehicles, etc., can solve the problems that the control strategy cannot achieve the optimal control effect, and the impact and expectations are different. , to achieve the effect of improving expressway traffic efficiency and reducing system traffic time
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[0013] The present invention is based on the basic principle of the reinforcement learning Q learning method and the basic process of the variable speed limit control strategy. It proposes a variable speed limit control strategy for the upstream of the bottleneck section, and detects the bottleneck section and its upstream and downstream traffic through a traffic flow detector. The training database is generated for the flow operation status. The agent learns the optimal variable speed limit value under different traffic flow conditions through offline learning. In actual control, the agent perceives the real-time traffic flow state through the measured traffic flow data on the express road. Select the optimal speed limit value corresponding to the current state to dynamically adjust the traffic flow, use the traffic flow data and speed limit value after the control is implemented to continuously train the agent, and based on the reinforcement learning variable speed limit contro...
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