{"title":"基于仿真的车辆交通信号灯优化","authors":"Dancho Panovski, T. Zaharia","doi":"10.1109/SITIS.2016.49","DOIUrl":null,"url":null,"abstract":"A great challenge today in urban areas and dense populated cities is determining an optimal traffic light system that can maximize the number of passing vehicles in a minimum amount of time. In this paper, we have addressed the issue of traffic flow management in urban areas by proposing as a solution a traffic light optimization method. The proposed approach uses the SUMO simulator as a cost-effective solution and a PSO optimization technique for traffic lights cycle program. A series of experimental simulations were performed with different number of vehicles in different time tables. The results obtained shows significant improvements in terms of increasing the number of vehicles that complete the simulation (4,5% to 10,5% of gain) and average journey time necessary for the vehicles to reach their destination (5,37% to 21,53% less time loss).","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Simulation-Based Vehicular Traffic Lights Optimization\",\"authors\":\"Dancho Panovski, T. Zaharia\",\"doi\":\"10.1109/SITIS.2016.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A great challenge today in urban areas and dense populated cities is determining an optimal traffic light system that can maximize the number of passing vehicles in a minimum amount of time. In this paper, we have addressed the issue of traffic flow management in urban areas by proposing as a solution a traffic light optimization method. The proposed approach uses the SUMO simulator as a cost-effective solution and a PSO optimization technique for traffic lights cycle program. A series of experimental simulations were performed with different number of vehicles in different time tables. The results obtained shows significant improvements in terms of increasing the number of vehicles that complete the simulation (4,5% to 10,5% of gain) and average journey time necessary for the vehicles to reach their destination (5,37% to 21,53% less time loss).\",\"PeriodicalId\":403704,\"journal\":{\"name\":\"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITIS.2016.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2016.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A great challenge today in urban areas and dense populated cities is determining an optimal traffic light system that can maximize the number of passing vehicles in a minimum amount of time. In this paper, we have addressed the issue of traffic flow management in urban areas by proposing as a solution a traffic light optimization method. The proposed approach uses the SUMO simulator as a cost-effective solution and a PSO optimization technique for traffic lights cycle program. A series of experimental simulations were performed with different number of vehicles in different time tables. The results obtained shows significant improvements in terms of increasing the number of vehicles that complete the simulation (4,5% to 10,5% of gain) and average journey time necessary for the vehicles to reach their destination (5,37% to 21,53% less time loss).