Study On Regional Signal Coordination Control Based On Multi-agent

With the rapid development of social economy,which caused the increasing number of vehicles in the city,leading to urban traffic problems become increasingly prominent.Congestion has become a major obstacle to urbanization and must be solved properly.In order to solve the problem fundamentally,scientific regulation and management must be adopted.Urban traffic has three typical characteristics--complexity,time-varying and uncertainty.Therefore,the traditional traffic control theory and methods cannot meet the requirements of the traffic in the city,so intelligent traffic control system has become necessary to resolve the problem.On the basis of the two kinds of multi-agent model,this paper designs a traffic model.In the model,four different types of agents are used to describe the traffic scene.Each agent can communicate with neighboring agents so as to ensure the sharing of traffic data.In order to ensure the real-time traffic signal scheme,each agent can quickly and accurately calculate a large number of traffic data.The purpose of regional coordination is to minimize the congestion in the area and to achieve the maximum flow throughout the region.According to the game theory and multi-agent traffic model,the coordination model is established,and the control strategy of each intersection is determined after the coordination of multiple agents.In the realization of intersection control strategy,the genetic algorithm is applied to each intersection signal,ultimately achieving optimal control of traffic areas.This paper uses VISSIM and VB to simulate the signal timing scheme.VISSM is the current mainstream traffic simulation tool,it can simulate the real traffic scene and obtain the relevant traffic parameters;such as the delay time,the time of parking and the speed of the vehicle.Through the analysis of traffic parameters,and compared with the traditional timing control method,it can be seen that the traffic control method proposed by the author is more effective and reasonable to reduce traffic congestion.