{"title":"预测用户目的地的汽车导航系统地图匹配算法","authors":"K. Miyashita, T. Terada, S. Nishio","doi":"10.1109/WAINA.2008.242","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a map matching algorithm for car navigation systems that predict user destination. This car navigation system is a novel system that automatically predicts user purpose and destination to present various information based on predicted purpose without user interaction. It requires the correct road where the car drives in real time, and it also need to know the route from the start point to the current point correctly. The proposal map matching method divides the trajectory into equal intervals and calculates the shortest path score for each one. Testing using GPS data for actual car trips showed that its use results in better destination prediction than with conventional methods in most cases. The results were the best for intervals of 5 minutes.","PeriodicalId":170418,"journal":{"name":"22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"A Map Matching Algorithm for Car Navigation Systems that Predict User Destination\",\"authors\":\"K. Miyashita, T. Terada, S. Nishio\",\"doi\":\"10.1109/WAINA.2008.242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a map matching algorithm for car navigation systems that predict user destination. This car navigation system is a novel system that automatically predicts user purpose and destination to present various information based on predicted purpose without user interaction. It requires the correct road where the car drives in real time, and it also need to know the route from the start point to the current point correctly. The proposal map matching method divides the trajectory into equal intervals and calculates the shortest path score for each one. Testing using GPS data for actual car trips showed that its use results in better destination prediction than with conventional methods in most cases. The results were the best for intervals of 5 minutes.\",\"PeriodicalId\":170418,\"journal\":{\"name\":\"22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WAINA.2008.242\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WAINA.2008.242","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Map Matching Algorithm for Car Navigation Systems that Predict User Destination
In this paper, we propose a map matching algorithm for car navigation systems that predict user destination. This car navigation system is a novel system that automatically predicts user purpose and destination to present various information based on predicted purpose without user interaction. It requires the correct road where the car drives in real time, and it also need to know the route from the start point to the current point correctly. The proposal map matching method divides the trajectory into equal intervals and calculates the shortest path score for each one. Testing using GPS data for actual car trips showed that its use results in better destination prediction than with conventional methods in most cases. The results were the best for intervals of 5 minutes.