Traffic signal lamp anti-blocking control method and system based on deep reinforcement learning

Abstract

The invention relates to a traffic signal lamp anti-blocking control method and system based on deep reinforcement learning. The data of each intersection is processed by an intersection decision controller of an intersection, the intersection decision controller transmits the processed result to a terminal decision device, the terminal decision device further processes the obtained data, and theterminal decision device only takes over the decision right when the congestion value or the predicted congestion value of the intersection is larger than a threshold value, so that the signal lamps in one area are uniformly controlled and managed. When the congestion value or the predicted congestion value is smaller than or equal to the threshold value, the signal lamp of each intersection is decided and controlled by the intersection decision controller of the intersection. The traffic signal lamp anti-blocking control method and system based on deep reinforcement learning can greatly shorten the data processing time and avoid the situation that the adjacent intersections are congested because only the maximum traffic of a single intersection is concerned. According to the invention, the traffic signal lamp anti-blocking control method and system based on deep reinforcement learning are beneficial to solving the problem of traffic jam.

Description

technical field [0001] The invention relates to the field of traffic information signal lamp control, in particular to a traffic signal lamp anti-blocking control method and system based on deep reinforcement learning. Background technique [0002] In cities, there are a large number of motor vehicles and non-motor vehicles, and the intersections and road sections are complicated. It is a very complicated task to deal with such a large-scale, dynamic, and highly uncertain distributed system for effective control. Work. In the case of no new traffic roads, it is an effective way to quickly solve urban traffic problems through reasonable traffic control to improve the utilization efficiency of roads, and then improve the traffic efficiency. [0003] At present, my country's cities adopt the traffic signal control mode. With the continuous development of the city and the continuous expansion of the traffic flow, the traditional traffic signal has problems in dispatching. One ...

AI Technical Summary

Problems solved by technology

[0005] Based on this, it is necessary to provide a traffic light anti-jamming control method based on deep reinforcement learning to solve the problem that the traditional signal light control method is still not ideal for alleviating traffic congestion.

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