Multi-intersection cooperative traffic light control method based on Q-value migration of multi-task deep Q network

Abstract

The invention, which belongs to the crossing field of artificial intelligence and intelligent transportation, provides a multi-intersection cooperative traffic light control method based on Q-value migration of a multi-task deep Q network. Multiple intersections are modeled into a multi-agent system; a multi-task network that is suitable for controlling of each intersection traffic light is trained at multiple intersections; knowledge learned at the multiple intersections is applied to a target problem, so that the multi-task network have much more knowledge than the single network and the single intersection feature extraction capacity is enhanced; and then on the basis of a cooperative algorithm, traffic lights of all intersections in a target area are controlled cooperatively. Therefore, the traffic flows of all intersections can be balanced to a certain degree; the road utilization rate in the regional traffic can be increased; the vehicle queuing length can be reduced; and the traffic congestion can be alleviated. The method has the high scalability to the traffic network.

Description

technical field [0001] The invention belongs to the intersecting field of artificial intelligence and intelligent transportation, and relates to a multi-task deep Q-network-based Q-value transfer multi-intersection signal light cooperative control method. Background technique [0002] Urban traffic runs through all areas of urban public space and is the most important and most convenient way for residents to travel daily. After long-term development, urban traffic has formed a relatively complete pattern, which improves the travel efficiency of residents and brings great benefits to residents' lives. convenient. However, with the development of the economy and the acceleration of urbanization, the urban population and the number of cars per capita are increasing rapidly, and the problem of traffic congestion is becoming more and more serious. . In order to alleviate traffic congestion, methods of expanding road infrastructure such as widening roads and building viaducts ca...

AI Technical Summary

Problems solved by technology

[0010] Aiming at the problems that the traditional signal light control method has difficulty in extracting traffic state features, the similarity between multiple agents in multi-intersections is not fully exploited, and the effective coordination strategy between multi-intersection signal lights is lacking, the present invention proposes a multi-intersection based Q-value transfer cooperative control method with task deep Q network (QT-MTDQN) for multi-intersection signal light cooperative control

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