{"title":"城市主干道行车时间预测","authors":"G. Jiang, Ruoqi Zhang","doi":"10.1109/ITSC.2003.1252725","DOIUrl":null,"url":null,"abstract":"Based on the relative relationship of the traffic volume of segments on the urban road network, we studied the optimal space distribution of detectors with statistic analysis techniques. Then we proposed the criteria of installing detectors on the urban roads, on the other hand, we predicted and checked out the non-detectors segment travel time using neural network technique of mix-structure algorithm with the data of the road network of Changchun City, China. The research gives a way to solve the optimal space distribution of detectors on urban arterial road and non-detected segment travel time prediction with detected segment traffic information.","PeriodicalId":123155,"journal":{"name":"Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Travel time prediction for urban arterial road\",\"authors\":\"G. Jiang, Ruoqi Zhang\",\"doi\":\"10.1109/ITSC.2003.1252725\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the relative relationship of the traffic volume of segments on the urban road network, we studied the optimal space distribution of detectors with statistic analysis techniques. Then we proposed the criteria of installing detectors on the urban roads, on the other hand, we predicted and checked out the non-detectors segment travel time using neural network technique of mix-structure algorithm with the data of the road network of Changchun City, China. The research gives a way to solve the optimal space distribution of detectors on urban arterial road and non-detected segment travel time prediction with detected segment traffic information.\",\"PeriodicalId\":123155,\"journal\":{\"name\":\"Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2003.1252725\",\"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 2003 IEEE International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2003.1252725","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Based on the relative relationship of the traffic volume of segments on the urban road network, we studied the optimal space distribution of detectors with statistic analysis techniques. Then we proposed the criteria of installing detectors on the urban roads, on the other hand, we predicted and checked out the non-detectors segment travel time using neural network technique of mix-structure algorithm with the data of the road network of Changchun City, China. The research gives a way to solve the optimal space distribution of detectors on urban arterial road and non-detected segment travel time prediction with detected segment traffic information.