{"title":"Cooperative localization based on topology matching","authors":"Seung-Tak Choi, Woo-Sol Hur, S. Seo","doi":"10.1109/WIVEC.2014.6953218","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new vehicle localization method based on topology matching in mutli-vehicle enviroment. Each vehicle is assumed to generate a local map which is a set of position measurements of nearby vehicles by using onboard low-cost GPS and ranging sensors, and share it with others by broadcasting via vehicle-to-vehicle(V2V) communication. When a vehicle receives multiple local maps from neighbors, it incorporates and fuses them with its own local map by using a local map matching algorithm. The proposed algorithm is based on the topology matching technique and the multi-sensor Kalman filter. Simulation results show that our method can extend the detection range and improve the position accuracy by 65% compared to conventional localization methods utilizing the Kalman filter with only onboard GPS measurements.","PeriodicalId":410528,"journal":{"name":"2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 6th International Symposium on Wireless Vehicular Communications (WiVeC 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIVEC.2014.6953218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper, we propose a new vehicle localization method based on topology matching in mutli-vehicle enviroment. Each vehicle is assumed to generate a local map which is a set of position measurements of nearby vehicles by using onboard low-cost GPS and ranging sensors, and share it with others by broadcasting via vehicle-to-vehicle(V2V) communication. When a vehicle receives multiple local maps from neighbors, it incorporates and fuses them with its own local map by using a local map matching algorithm. The proposed algorithm is based on the topology matching technique and the multi-sensor Kalman filter. Simulation results show that our method can extend the detection range and improve the position accuracy by 65% compared to conventional localization methods utilizing the Kalman filter with only onboard GPS measurements.