Research On Optimization Method Of Traffic Signal Control In Urban Area

With the rapid development of social economy,the number of vehicles in the urban road network has increased rapidly,the existing road conditions are difficult to meet the traffic demand,and the problem of urban congestion has become increasingly serious,which restricts the further development of the urban economy and reduces the happiness index of urban life.Therefore,it is of great significance to study the optimization method of traffic signal control in urban areas.This paper studies the urban regional traffic signal control strategy and intelligent optimization algorithm from two aspects:single intersection and urban arterial traffic.The main work of the dissertation is as follows:(1)Describe the research background and the significance of the paper,and analyze and summarize the development status of intersection signal control from the two aspects of signal timing model and optimization algorithm.(2)Aiming at the problem that particle swarm optimization algorithm has prominent global optimization ability and low dependence on the problem,but the convergence rate decreases at the late iteration stage,and premature convergence is easy to occur.Taking advantage of the powerful local search ability of the variable neighborhood search algorithm,an adaptive variable neighborhood particle swarm optimization algorithm is proposed.Six Benchmark functions are selected to verify the convergence speed and convergence precision of the proposed algorithm,and compare with some improved particle swarm optimization algorithms.The results show that the algorithm has obvious superiority in solving complex nonlinear functions.(3)On the basis of analyzing the traffic signal control theory,a four-phase intersection signal timing optimization model is established with the minimum total vehicle delay time as the optimization objective.And the particle swarm optimization algorithm and adaptive variable neighborhood search particle swarm optimization algorithm are used to optimize the two control strategies of fixed period and indefinite period respectively.The data experimental show that the optimization effect of the indefinite period control is better than the optimization effect of the fixed period control and timing control from the control strategy.In terms of optimization algorithm,the optimization effect of the proposed algorithm is superior to particle swarm optimization algorithm and timing control.(4)On the basis of the theory and method of arterial signal coordinated control,the two control strategies are optimized by optimizing the phase difference separately and phase difference and the coordinated phase green time jointly.The optimization model of the arterial signal coordination control is established,and optimized by the proposed algorithm.The data experiments show that the control effect ofj oint optimization is better than that the single optimization,and the control effect of the single optimization is better than that timing control,and the optimization effect of adaptive variable neighborhood search particle swarm optimization algorithm is better than that of particle swarm optimization algorithm.At the same time,this paper considers the vehicle delay of coordinated phase and non-coordinated phase in the form of weight ratio.The experimental results show that when properly considering the influence of uncoordinated phase delay,the delay time of the trunk line can be reduced as a whole,and the traffic efficiency of the road network can be improved.(5)Finally,the traffic optimization simulation platform based on VISSIM is established through the COM interface of vissim,and the VISSIM simulation model of single intersection and arterial traffic coordination control is eatablished respectively to verify the effectiveness of the control strategy and optimization algorithm adopted in this paper.