Pavement traffic signal lamp coordination control method based on reinforcement learning

Abstract

The invention discloses a pavement traffic signal lamp coordination control method based on reinforcement learning. Monitoring equipment which is arranged correspondingly to each crossing is included. Each monitoring equipment is connected to a remote server through a network module. The control method comprises the following steps that (1) the remote server calculates waiting time S through receiving a video signal; (2) the remote server analyzes and acquires a road congestion condition under each phase state ai; (3) the remote server acquires a feasible degree ciai under the phase state ai; when a traffic stream can pass through, the road is clear and the feasible degree ciai is 1; otherwise, congestion is generated in the road and the feasible degree ciai is 0; (4) the waiting time S and the feasible degree ciai are used to calculate an optimal driving phase state ai of the crossing; (5) the signal lamp is adjusted. The method in the invention is based on video information acquired in real time. Through coordinating and controlling traffic signal lamps of the plurality of crossings in one area, traffic passing efficiency is increased; a traffic flow of the area is maximized and a pavement traffic congestion condition is alleviated.

Description

technical field [0001] The invention relates to a method for controlling road traffic signal lamps, in particular to a method for coordinated control of road traffic signal lamps based on reinforcement learning. Background technique [0002] Traffic is the foundation of modern society and the lifeblood of human society and economy. People's social behavior is closely related to traffic. In a city, there are a large number of motor vehicles and non-motor vehicles, and the intersections and road sections are complicated. It is very complicated 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] However, traffic congestion and congestion are becoming more and more serious now. The reasons...

AI Technical Summary

Problems solved by technology

These factors will cause some intersections to pass poorly, or even paralyzed

At present, many traffic management departments can only rely on manpower to direct on-site and directly control the changes of signal lights manually.

However, manual management of traffic lights is likely to cause omissions; at the same time, manual management of traffic lights generally only manages the signal lights of a single intersection, and it is difficult to achieve coordinated control of regional signal lights. Due to the heavy traffic ahead, the embarrassing situation of still encountering congestion

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