{"title":"用于实时车辆轨迹估算和预测的汽车跟踪信息神经网络","authors":"Yu-Hang Yin, Xing Lü, Shu-Kai Li, Li-Xing Yang, Ziyou Gao","doi":"10.1080/23249935.2024.2374523","DOIUrl":null,"url":null,"abstract":"Vehicle trajectory information is a crucial part of improving the efficiency and the safety of the ITS. Data missing or irregular sampling in the real-world road traffic makes it hard to obtain acc...","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"51 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Car-following informed neural networks for real-time vehicle trajectory imputation and prediction\",\"authors\":\"Yu-Hang Yin, Xing Lü, Shu-Kai Li, Li-Xing Yang, Ziyou Gao\",\"doi\":\"10.1080/23249935.2024.2374523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicle trajectory information is a crucial part of improving the efficiency and the safety of the ITS. Data missing or irregular sampling in the real-world road traffic makes it hard to obtain acc...\",\"PeriodicalId\":48871,\"journal\":{\"name\":\"Transportmetrica A-Transport Science\",\"volume\":\"51 1\",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportmetrica A-Transport Science\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/23249935.2024.2374523\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica A-Transport Science","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/23249935.2024.2374523","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Car-following informed neural networks for real-time vehicle trajectory imputation and prediction
Vehicle trajectory information is a crucial part of improving the efficiency and the safety of the ITS. Data missing or irregular sampling in the real-world road traffic makes it hard to obtain acc...
期刊介绍：
Transportmetrica A provides a forum for original discourse in transport science. The international journal''s focus is on the scientific approach to transport research methodology and empirical analysis of moving people and goods. Papers related to all aspects of transportation are welcome. A rigorous peer review that involves editor screening and anonymous refereeing for submitted articles facilitates quality output.
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