Full metadata record
DC FieldValueLanguage
dc.contributor.authorChang, Yu-Mingen_US
dc.contributor.authorWei, Ling-Yinen_US
dc.contributor.authorLin, Chun-Shuoen_US
dc.contributor.authorJung, Chen-Henen_US
dc.contributor.authorChen, I-Hungen_US
dc.contributor.authorPeng, Wen-Chihen_US
dc.date.accessioned2014-12-08T15:23:54Z-
dc.date.available2014-12-08T15:23:54Z-
dc.date.issued2009en_US
dc.identifier.isbn978-1-4244-4153-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/16628-
dc.description.abstractTraffic status plays an important role in navigation systems. To estimate traffic status, expensive sensors are deployed, which is not cost efficient. In view of the growth of GPS navigation services, in this paper, we propose two algorithms to estimate traffic status of road segments in our CarWeb platform. To evaluate our proposed algorithms, we implement the proposed algorithms in our CarWeb platform that is used to collect GPS data points from cars. Extensive experiments are conducted on real datasets and experimental results indicate that our algorithms can provide desirable predictions of traffic status.en_US
dc.language.isoen_USen_US
dc.titleExploring GPS Data for Traffic Status Estimationen_US
dc.typeProceedings Paperen_US
dc.identifier.journalMDM: 2009 10TH INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENTen_US
dc.citation.spage369en_US
dc.citation.epage370en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000273978000049-
Appears in Collections:Conferences Paper