{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T05:28:18Z","timestamp":1740461298035,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>As economy and construction rapidly grow, traffic problems become seri ous increasingly. To predict the traffic condition, it is particularly important to estimate the traffic volume. At present, GPS technology has good prospects in traffic information collection, vehicle guidance and so on. In this paper, a model is established based on vehicle information collected by GPS floating cars. The traffic volume is estimated by the number of vehicles between two floating cars. This method is easy to operate and has good real-time performance. The model is verified by comparing the estimated data with the measured data.<\/jats:p>","DOI":"10.3233\/978-1-61499-939-3-249","type":"book-chapter","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T11:59:50Z","timestamp":1740398390000},"source":"Crossref","is-referenced-by-count":0,"title":["Expressway Traffic Volume Prediction Using Floating Car Trajectory Data"],"prefix":"10.3233","author":[{"family":"Yuan Xianghong","sequence":"additional","affiliation":[]},{"family":"Yan Xiaoxiao","sequence":"additional","affiliation":[]},{"family":"Li Yang","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Technology and Intelligent Transportation Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T12:12:23Z","timestamp":1740399143000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-938-6&spage=249&doi=10.3233\/978-1-61499-939-3-249"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-939-3-249","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2019]]}}}