{"title":"如何将实时交通信息转换成用于动态路由的历史数据库","authors":"L. Rothkrantz","doi":"10.1109/InfoTech.2019.8860873","DOIUrl":null,"url":null,"abstract":"Most routing devices use real time traffic information. It proved that the first hours of a new day can be used to find a good matching day in the past. The traffic data from the matching day can be used to predict traffic streams on the current day. We designed a historic database storing traffic information from real time available public domain databases. A dynamic version of the well-known Dijkstra shortest path algorithm was used to design a dynamic routing algorithm.","PeriodicalId":179336,"journal":{"name":"2019 International Conference on Information Technologies (InfoTech)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"How to Transform Real Time Traffic Information into a Historical Database Used for Dynamic Routing\",\"authors\":\"L. Rothkrantz\",\"doi\":\"10.1109/InfoTech.2019.8860873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most routing devices use real time traffic information. It proved that the first hours of a new day can be used to find a good matching day in the past. The traffic data from the matching day can be used to predict traffic streams on the current day. We designed a historic database storing traffic information from real time available public domain databases. A dynamic version of the well-known Dijkstra shortest path algorithm was used to design a dynamic routing algorithm.\",\"PeriodicalId\":179336,\"journal\":{\"name\":\"2019 International Conference on Information Technologies (InfoTech)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Information Technologies (InfoTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/InfoTech.2019.8860873\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Information Technologies (InfoTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InfoTech.2019.8860873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How to Transform Real Time Traffic Information into a Historical Database Used for Dynamic Routing
Most routing devices use real time traffic information. It proved that the first hours of a new day can be used to find a good matching day in the past. The traffic data from the matching day can be used to predict traffic streams on the current day. We designed a historic database storing traffic information from real time available public domain databases. A dynamic version of the well-known Dijkstra shortest path algorithm was used to design a dynamic routing algorithm.
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