{"title":"基于VANETs的实时交通估计车辆路径规划解决方案","authors":"Zongjian He, Jiannong Cao, Tao Li","doi":"10.1109/ICCVE.2012.39","DOIUrl":null,"url":null,"abstract":"Dynamic vehicular path planning using real-time traffic information have attracted the interest for both academic and industry. How to collect traffic information and make path planning decisions accordingly are two major problems. Existing works have addressed these issues using centralized or infrastructure based traffic collection approaches. However, existing works have certain weaknesses on efficiency and effectiveness. This paper introduced a novel dynamic vehicular path planning solution. The proposed solution does not rely on infrastructures to collect traffic information. Meanwhile, It utilizes density-speed traffic flow model to predict the traffic condition. In addition, a dynamic candidate path selection algorithm is developed to reduce the redundant data collection overhead. Extensive evaluations using large scale traffic trace based simulation have been performed. The results show that our solution outperforms some existing solutions in terms of communication efficiency and path planning effectiveness.","PeriodicalId":182453,"journal":{"name":"2012 International Conference on Connected Vehicles and Expo (ICCVE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"MICE: A Real-time Traffic Estimation Based Vehicular Path Planning Solution Using VANETs\",\"authors\":\"Zongjian He, Jiannong Cao, Tao Li\",\"doi\":\"10.1109/ICCVE.2012.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic vehicular path planning using real-time traffic information have attracted the interest for both academic and industry. How to collect traffic information and make path planning decisions accordingly are two major problems. Existing works have addressed these issues using centralized or infrastructure based traffic collection approaches. However, existing works have certain weaknesses on efficiency and effectiveness. This paper introduced a novel dynamic vehicular path planning solution. The proposed solution does not rely on infrastructures to collect traffic information. Meanwhile, It utilizes density-speed traffic flow model to predict the traffic condition. In addition, a dynamic candidate path selection algorithm is developed to reduce the redundant data collection overhead. Extensive evaluations using large scale traffic trace based simulation have been performed. The results show that our solution outperforms some existing solutions in terms of communication efficiency and path planning effectiveness.\",\"PeriodicalId\":182453,\"journal\":{\"name\":\"2012 International Conference on Connected Vehicles and Expo (ICCVE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Connected Vehicles and Expo (ICCVE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCVE.2012.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Connected Vehicles and Expo (ICCVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCVE.2012.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MICE: A Real-time Traffic Estimation Based Vehicular Path Planning Solution Using VANETs
Dynamic vehicular path planning using real-time traffic information have attracted the interest for both academic and industry. How to collect traffic information and make path planning decisions accordingly are two major problems. Existing works have addressed these issues using centralized or infrastructure based traffic collection approaches. However, existing works have certain weaknesses on efficiency and effectiveness. This paper introduced a novel dynamic vehicular path planning solution. The proposed solution does not rely on infrastructures to collect traffic information. Meanwhile, It utilizes density-speed traffic flow model to predict the traffic condition. In addition, a dynamic candidate path selection algorithm is developed to reduce the redundant data collection overhead. Extensive evaluations using large scale traffic trace based simulation have been performed. The results show that our solution outperforms some existing solutions in terms of communication efficiency and path planning effectiveness.