{"title":"基于ACP的城市交叉口自学习控制","authors":"Feng Chen, Lingyun Zhu, C. Han, Xiong Gang","doi":"10.1109/SOLI.2014.6960744","DOIUrl":null,"url":null,"abstract":"The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.","PeriodicalId":191638,"journal":{"name":"Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ACP based self-learning control for urban intersection\",\"authors\":\"Feng Chen, Lingyun Zhu, C. Han, Xiong Gang\",\"doi\":\"10.1109/SOLI.2014.6960744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.\",\"PeriodicalId\":191638,\"journal\":{\"name\":\"Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOLI.2014.6960744\",\"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 2014 IEEE International Conference on Service Operations and Logistics, and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2014.6960744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ACP based self-learning control for urban intersection
The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.