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Surv."],"published-print":{"date-parts":[[2025,9,30]]},"abstract":"<jats:p>Vehicles traveling through cities generate extensive vehicle trajectory collected by scalable sensors, providing excellent opportunities to address urban challenges such as traffic congestion and public safety. In this survey, we systematically review vehicle trajectory collection, preprocessing, analytics, and applications. First, we focus on the standard techniques for vehicle trajectory collection and corresponding datasets. Next, we introduce representative approaches for the latest advances in vehicle trajectory processing. We further discuss individual travel behavior and collective mobility analytics using vehicle trajectory. Since private cars constitute the majority of urban vehicles and form the basis for many recent research findings, we emphasize analytics based on private car trajectory data. We then compile vehicle trajectory-boosted applications from the perspective of computing vehicle trajectory. Finally, we go through unresolved problems with vehicle trajectory and outline potential future research directions.<\/jats:p>","DOI":"10.1145\/3715902","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T06:34:23Z","timestamp":1741242863000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Vehicle Trajectory Data Processing, Analytics, and Applications: A Survey"],"prefix":"10.1145","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8742-337X","authenticated-orcid":false,"given":"Chenxi","family":"Liu","sequence":"first","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5645-160X","authenticated-orcid":false,"given":"Zhu","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0223-456X","authenticated-orcid":false,"given":"Wangchen","family":"Long","sequence":"additional","affiliation":[{"name":"The College of Artificial Intelligence, Zhuhai City Polytechnic, Zhuhai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4343-703X","authenticated-orcid":false,"given":"Tong","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7372-2539","authenticated-orcid":false,"given":"Hongbo","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5224-4048","authenticated-orcid":false,"given":"Keqin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, State University of New York, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"key":"e_1_3_2_2_2","article-title":"A survey on spatio-temporal data analytics systems","author":"Alam Md Mahbub","year":"2021","unstructured":"Md Mahbub Alam, Luis Torgo, and Albert Bifet. 2021. 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