{"title":"实时综合和预期交通管理的框架","authors":"H. Taale, S. Hoogendoorn","doi":"10.1109/ITSC.2013.6728272","DOIUrl":null,"url":null,"abstract":"This paper presents a framework for real-time integrated and anticipatory traffic management. It uses model predictive control including route choice to optimize traffic management. It is tested for one small network with good results. Simulations varying the prediction horizon, the number of iterations of the assignment within the optimization loop and the optimization criterion were conducted and results of these simulations are given. The framework can be used as a basis for further research on this topic.","PeriodicalId":275768,"journal":{"name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A framework for real-time integrated and anticipatory traffic management\",\"authors\":\"H. Taale, S. Hoogendoorn\",\"doi\":\"10.1109/ITSC.2013.6728272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a framework for real-time integrated and anticipatory traffic management. It uses model predictive control including route choice to optimize traffic management. It is tested for one small network with good results. Simulations varying the prediction horizon, the number of iterations of the assignment within the optimization loop and the optimization criterion were conducted and results of these simulations are given. The framework can be used as a basis for further research on this topic.\",\"PeriodicalId\":275768,\"journal\":{\"name\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2013.6728272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2013.6728272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A framework for real-time integrated and anticipatory traffic management
This paper presents a framework for real-time integrated and anticipatory traffic management. It uses model predictive control including route choice to optimize traffic management. It is tested for one small network with good results. Simulations varying the prediction horizon, the number of iterations of the assignment within the optimization loop and the optimization criterion were conducted and results of these simulations are given. The framework can be used as a basis for further research on this topic.