{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T14:44:55Z","timestamp":1761489895201},"reference-count":0,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,1,1]]},"abstract":"<p>With the growing popularity of cell phones, using massive cellular signaling data as probe to track the vehicles movement trajectory and obtain the real-time traffic condition has become one of the most attractive candidate techniques. However, traditional approaches may offer a poor performance in removing noisy data and minimizing deviation of traffic speed in adjacent time intervals. In this paper, a novel approach is proposed to solve these two issues. The authors move noisy data by comparing the cellular signaling data with the trained data set, and adopt a modified Kalman filter algorithm to minimize the deviations. The experiment results show that the accuracy of the approach performs better in comparison to other two traffic speed estimation approaches.<\/p>","DOI":"10.4018\/ijwsr.2016010105","type":"journal-article","created":{"date-parts":[[2016,1,25]],"date-time":"2016-01-25T17:26:44Z","timestamp":1453742804000},"page":"69-87","source":"Crossref","is-referenced-by-count":4,"title":["A Novel Freeway Traffic Speed Estimation Model with Massive Cellular Signaling Data"],"prefix":"10.4018","volume":"13","author":[{"given":"Tongyu","family":"Zhu","sequence":"first","affiliation":[{"name":"State Key Lab of Software Development Environment, Beihang University, Beijing, China"}]},{"given":"Zhixin","family":"Song","sequence":"additional","affiliation":[{"name":"State Key Lab of Software Development Environment, Beihang University, Beijing, China"}]},{"given":"Dongdong","family":"Wu","sequence":"additional","affiliation":[{"name":"Beijing Transportation Information Center, Beijing, China"}]},{"given":"Jianjun","family":"Yu","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China"}]}],"member":"2432","container-title":["International Journal of Web Services Research"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=144873","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T19:05:47Z","timestamp":1654110347000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJWSR.2016010105"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2016,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijwsr.2016010105","relation":{},"ISSN":["1545-7362","1546-5004"],"issn-type":[{"value":"1545-7362","type":"print"},{"value":"1546-5004","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,1]]}}}