{"title":"Traffic Light Timing Optimization based on Improved Particle Swarm Optimization","authors":"Chi Liu, Changqing Yan, Chenyin Ma, Qihan Suo","doi":"10.1109/IAEAC54830.2022.9929570","DOIUrl":null,"url":null,"abstract":"Intersections are one of the important factors affecting the overall traffic efficiency of road sections. To alleviate the pressure on road traffic and improve the traffic efficiency of intersections, this paper proposes an optimization model of signal light timing from three aspects of road, vehicle and environment, selects road capacity, average delay and vehicle carbon emissions as optimization goals. In addition, this paper proposes an improved particle swarm optimization to solve the model. Add adaptive weights to the particle swarm optimization, update the particle position by levy flight to improve the ability of the algorithm. The experimental results show that the timing scheme obtained by using the improved particle swarm optimization algorithm is superior to other methods in terms of convergence speed and convergence accuracy, which proves the feasibility and superiority of the algorithm.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"32 1-2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC54830.2022.9929570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Intersections are one of the important factors affecting the overall traffic efficiency of road sections. To alleviate the pressure on road traffic and improve the traffic efficiency of intersections, this paper proposes an optimization model of signal light timing from three aspects of road, vehicle and environment, selects road capacity, average delay and vehicle carbon emissions as optimization goals. In addition, this paper proposes an improved particle swarm optimization to solve the model. Add adaptive weights to the particle swarm optimization, update the particle position by levy flight to improve the ability of the algorithm. The experimental results show that the timing scheme obtained by using the improved particle swarm optimization algorithm is superior to other methods in terms of convergence speed and convergence accuracy, which proves the feasibility and superiority of the algorithm.