Regional Traffic Signal Optimization Control Based On Phase Difference Coordination Mechanism

With the rapid development of the city,the urban traffic network becomes more and more complex and the traffic volume is getting larger and larger.The existing traffic control system is gradually unable to meet the actual demand,causing increasingly serious road congestion.The research of regional traffic intelligent control technology is an effective way to solve this problem.In view of the difficulty in the close coordination control of the existing regional traffic coordination control technology,this paper presents an improved HCM2000 delay model based on the phase difference coordination of dynamic stochastic traffic flow.Genetic particle swarm optimization algorithm is used to optimize the coordinated control time scheme,which realizes the coordinated and optimal control of all intersections in the sub-region by phase difference,effectively reduce the average vehicle delay of regional road network.The main research contents are as follows:First of all,Aiming at the lack of consideration of the phase difference factor in the HCM2000 model of regional traffic coordination control,an improved HCM2000 delay model based on dynamic random flow phase difference coordination is proposed.Firstly,the traffic flow in the road network is divided into two parts: the inner intersection traffic flow and the marginal traffic flow.By introducing the phase difference coordination mechanism of dynamic stochastic traffic flow,all intersections in the whole road network are correlated;Then use mixed integer nonlinear optimization vehicle delay model,Make it suitable for sub-area entrance traffic flow volatility.Taking the shortest average delay of vehicles in the sub-area as the optimization objective,a coordinated control model of sub-area traffic signals based on phase difference was established.Secondly,Aiming at the optimization of the regional traffic coordination control,a hybrid optimization algorithm of genetic particle swarm is proposed.In order to enhance the diversity of the population and improve the global search ability of the algorithm,a multi-stage evolutionary strategy for the genetic operation of the algorithm is adopted.In order to ensure that good individuals do not lose and enhance population diversity,selective crossover operations are introduced after population particles velocity and position are iteratively updated.The fitness value sorting mechanism is used to divide and merge the populations,the advantages of genetic algorithm and particle swarm algorithm are fully utilized,so that the hybrid algorithm has a stronger ability of optimization.Simulation results show that the proposed genetic particle swarm optimization algorithm can obtain better coordination control time allocation scheme.Finally,Based on the VisSim microscopic traffic simulation software platform,a regional coordinated optimization control system based on the above-mentioned coordinated control model and its optimization algorithm was constructed.A sub-area road network object,a signal timing output module,a sub-area signal coordination and optimization module,and a sub-area coordination controller module were constructed,and system simulation was implemented.The experimental results show that the coordinated optimal control model and method proposed in this paper can effectively reduce the regional vehicle delay and improve the traffic efficiency of the regional road network.