Arterial Traffic Signal Coordination Optimization Control Based On Multi-Objective Particle Swarm

Arterial traffic signal coordination control is an important part of intelligent transportation system(ITS),and it plays a significant role in relieving traffic congestion?reducing environmental pollution and improving traffic efficiency of intersection and highway network.In addition,with the developing of the control theory,all kinds of modern intelligent control methods and intelligent optimization algorithms are used in traffic control and the signal timing of control system.As a result,in this article,we have a research on the urban traffic signal control,especially on the arterial traffic signal coordination control.The paper introduces the basic theories of road traffic signal control at length,through analyzing the evaluation criterion of the traffic signal control,we adopt the delay and the number of stops as the targets of the optimization.Aiming at the minimal delay of vehicles at arterial crossings,the paper proposes a model by dividing offset into leading offset and lagging offset.Aiming at the minimal number of stops of the vehicles at arterial crossings,the paper proposes a model by dividing stops into complete stops and incomplete stops.By using these two models in combination,we can get the multi-objective models based on delay and the number of the stops.According to the characteristics of the established optimization model,the multi-objective particle swarm optimization algorithm is designed to solve the multi-objective optimization model.In order to renew and maintain the particle repository(the secondary of our algorithm),we adopt the technology of the adaptive grids.After that,some related numerical experiments on the algorithm are performed combined with practical cases and the results of experiments are analyzed and summarized in the paper.Finally,we established the simulation and optimization model corresponding to the practical cases by using the software vissim which is specially used in traffic simulation.The result of simulation proves that our theoretical model is correct and using the arterial traffic coordination optimization control is efficient in improving the condition of the traffic.