{"title":"基于ITS的高效动态红绿灯控制","authors":"Naushin Nower, Sakhawat Hossan","doi":"10.1145/3018896.3056807","DOIUrl":null,"url":null,"abstract":"In almost all modern cities around the world, traffic congestion is a severe problem. Existing adaptive traffic control systems utilized traffic phase and phase duration either considering traffic density or vehicular waiting time and hunger level, without any optimization. To solve this problem, we have proposed an efficient dynamic traffic light control for ITS by considering multiple factors at a time with the provisions to optimize the average vehicular waiting time, and maximize throughput. Moreover, phase duration is set in such a way so that maximum people will get benefit. Simulation results demonstrate that our algorithm produces much higher throughput and lower vehicle's average waiting time, compared with that of other adaptive algorithms.","PeriodicalId":131464,"journal":{"name":"Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Efficient dynamic traffic light control for ITS\",\"authors\":\"Naushin Nower, Sakhawat Hossan\",\"doi\":\"10.1145/3018896.3056807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In almost all modern cities around the world, traffic congestion is a severe problem. Existing adaptive traffic control systems utilized traffic phase and phase duration either considering traffic density or vehicular waiting time and hunger level, without any optimization. To solve this problem, we have proposed an efficient dynamic traffic light control for ITS by considering multiple factors at a time with the provisions to optimize the average vehicular waiting time, and maximize throughput. Moreover, phase duration is set in such a way so that maximum people will get benefit. Simulation results demonstrate that our algorithm produces much higher throughput and lower vehicle's average waiting time, compared with that of other adaptive algorithms.\",\"PeriodicalId\":131464,\"journal\":{\"name\":\"Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3018896.3056807\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3018896.3056807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In almost all modern cities around the world, traffic congestion is a severe problem. Existing adaptive traffic control systems utilized traffic phase and phase duration either considering traffic density or vehicular waiting time and hunger level, without any optimization. To solve this problem, we have proposed an efficient dynamic traffic light control for ITS by considering multiple factors at a time with the provisions to optimize the average vehicular waiting time, and maximize throughput. Moreover, phase duration is set in such a way so that maximum people will get benefit. Simulation results demonstrate that our algorithm produces much higher throughput and lower vehicle's average waiting time, compared with that of other adaptive algorithms.