{"title":"利用智能手机上的气压计进行地铁列车在线定位的方法","authors":"S. Hyuga, Masaki Ito, M. Iwai, K. Sezaki","doi":"10.1145/2996913.2996999","DOIUrl":null,"url":null,"abstract":"Knowing the location of a train is necessary for the development of useful services for train passengers. However, popular localization methods such as GPS and Wi-Fi are not accurate, especially on a subway. This paper proposes an online algorithm for localization on a subway using only a barometer. We estimate the motion state from the change of elevation, then estimate the last station stopped at using the similarity of a series of elevations recorded when the train stopped to the actual elevations of the stations. We evaluated the proposed method using data from the subway in Tokyo. We also developed a mobile application to demonstrate the proposed method.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An online localization method for a subway train utilizing the barometer on a smartphone\",\"authors\":\"S. Hyuga, Masaki Ito, M. Iwai, K. Sezaki\",\"doi\":\"10.1145/2996913.2996999\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Knowing the location of a train is necessary for the development of useful services for train passengers. However, popular localization methods such as GPS and Wi-Fi are not accurate, especially on a subway. This paper proposes an online algorithm for localization on a subway using only a barometer. We estimate the motion state from the change of elevation, then estimate the last station stopped at using the similarity of a series of elevations recorded when the train stopped to the actual elevations of the stations. We evaluated the proposed method using data from the subway in Tokyo. We also developed a mobile application to demonstrate the proposed method.\",\"PeriodicalId\":20525,\"journal\":{\"name\":\"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2996913.2996999\",\"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 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2996913.2996999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An online localization method for a subway train utilizing the barometer on a smartphone
Knowing the location of a train is necessary for the development of useful services for train passengers. However, popular localization methods such as GPS and Wi-Fi are not accurate, especially on a subway. This paper proposes an online algorithm for localization on a subway using only a barometer. We estimate the motion state from the change of elevation, then estimate the last station stopped at using the similarity of a series of elevations recorded when the train stopped to the actual elevations of the stations. We evaluated the proposed method using data from the subway in Tokyo. We also developed a mobile application to demonstrate the proposed method.