Research And Simulation On Coordination Optimization Control Strategy Of Urban Regional Traffic Signal

With the development of modernization,the current urban traffic management levelhas been unable to alleviate the road congestion caused by the sharp increase in the number of motor vehicles.Using intelligent traffic control strategy is an effective method to improve the efficiency of traffic operation at present,and urban regional traffic coordination control isone ofthe important control strategies.A regional traffic signal control model based on the target relative dominance strategy is constructed,and a dual-population genetic algorithm based on the golden ratio is proposed.The signal units at the overall intersections within the region are coordinated and optimized.It can increase the total traffic capacity of the region,reduce the total delay time of vehicles in the area,and improve the overall network operation efficiency.The main research contents are as follows:Firstly,aiming at the problem of signal timing optimization in urban area with non-uniform traffic flow,the geographical characteristics of regional traffic and the information of intersections traffic flow are analyzed.A multi-objective optimization model of regional traffic signal coordination control is established.The model takes the total capacity and total delay time in the area as the target,and takes the period,phase and phase difference as the control variables.According to the characteristics of solving the optimal solution of the multi-objective optimization problem,a regional traffic signal control model based on the target relative dominance strategy is proposed.Combining with genetic algorithm,the signal light group of regional road network is coordinated and optimized.The experimental results verify the feasibility of the model and the utility of the genetic algorithmto solve the model.Secondly,aiming at the defects of genetic algorithm and combining the characteristics of the complex regional road network model,a dual-population genetic algorithm based on golden ratio is designed.The dual-population genetic algorithm is adopted.The golden ratio is introduced to improve the daul-population genetic algorithm.The main population was optimized globally by the improved dynamic crossover and mutation operator,and the secondary population was optimized locally by anmethodbased on the golden ratio.At the same time,the diversity of the population is increased by the migration of individuals between the two populations.Using four commonly used test functions for verification,the results show that the algorithm has global search and fast convergence performance.Then the algorithm is used to coordinate and optimize the control of regional signals.The experimental results show that the proposedalgorithm can quickly obtain a moreeffective coordinated optimal timing scheme and improve the control performance of regional traffic coordinated control.Finally,in order to intuitively reflect the traffic operating conditions under the intelligent traffic control strategy,the intuitiveness of the traffic simulation software VISSIM and the accuracy of MATLAB are fully utilized.The interface technology and co-simulation technology of VISSIM and MATLAB are studied.A regional intersection signal coordinated control simulation platform based on MATLAB and VISSIM co-simulation is built.A regional coordinated optimal control system based on the above-mentioned signal coordinated control model and optimization algorithm is implemented.The simulation results provethe performance of the proposed control model and optimization algorithm.It can effectively increase the traffic capacityof the road network,reduce the delay time of the road network,and improve the efficiency of traffic operation.