Study On The Multi-objective Signal Real-time Control For Intersections Based On Improved Particle SWARM Alogorithm

Recently,urban traffic congestion problem has become a serious social problem.The intersection is the key node of city road network.According to the dynamic traffic flow,real-time adjustment of signal timing can effectively improve the operation efficiency of the road.The existing signal control models used the optimization of the evaluation index as goals,and the papers built the single objective or multi-objective optimization model.Besides,these multi-objective optimization models are mostly weighted into single objective to solve,or solved by fixed timing under the static traffic flow condition,not dynamically adjusted according to the real-time change of the intersection traffic flow.In order to effectively improve the operating efficiency of the intersection,this paper proposes a real time control model of intersection based on improved particle swarm optimization algorithm,more details are as follows:Analyze the current research status of intersection signal control at domestic and abroad,and analyze the basic concept of intersection signal control and three main indicators.Through the introduction of the main algorithm of intersection signal control model,this paper finds the advantages of particle swarm optimization algorithm,which lays the theoretical foundation for this study.Improve particle swarm optimization algorithm and set up the model.Aiming at the problems existing in the multi-objective signal control model,and considering all factors affecting this model,and describing this problem,this paper proposes a real time signal control model for intersection based the goals of the minimal intersection delay,parking number and the maximum capacity,and this paper uses multi-objective particle swarm optimization based on Pareto algorithm to solve the model.Through variable definition,position,velocity updating and parameter setting,this paper has described the algorithm process combined with the principle of particle swarm optimization algorithm.Finally,an example is used to verify the multi-objective signal control model,and the inertia weight coefficient and acceleration constant are determined by Matlab programming.After determining the particle swarm algorithm finally configuration parameters,this paper compares the results of the optimal timing solution with present timing solution,and compares the signal control model in the past papers which transformed the multi-objective problem into single objective problem with the model proposed in this paper,as a result,this paper concludes the superiority of this model and the algorithm used.The study can achieve real-time change of signal timing,and effectively improve the utilization rate of the signal,so as to reduce the average delay of intersection,the average number of parking,and increase the effective capacity of each phase,effectively improve the efficiency of the intersection.