dc.contributor.authorTang, Youze
dc.contributor.authorZhu, Andy Diwen
dc.contributor.authorXiao, Xiaokui
dc.date.accessioned2013-10-04T08:18:41Z
dc.date.available2013-10-04T08:18:41Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationTang, Y., Zhu, A. D., & Xiao, X. (2012). An efficient algorithm for mapping vehicle trajectories onto road networks. Proceedings of the 20th International Conference on Advances in Geographic Information Systems, 601-604.
dc.identifier.urihttp://hdl.handle.net/10220/16294
dc.description.abstractModern mobile technology has enabled the collection of large scale vehicle trajectories using GPS devices. As GPS measurements may come with error, vehicle trajectories are often noisy. A common practice to alleviate this issue is to apply map-matching, i.e., to align vehicle trajectories with the road segments in a digitized road network. This paper presents an efficient solution for map-matching problem that won the SIGSPATIAL CUP 2012. Given a road network, our solution first constructs a gird index on the road segments. For each point p on a vehicle trajectory, we employ the index to identify a candidate set of road segments that are close to p, and then we refine the candidate set to select a segment that matches p with the highest probability. The selection of the best match is based on a metric that takes into account (i) the correlation between consecutive GPS measurements as well as (ii) the directions and shapes of the road segments. Experimental results on real vehicle trajectories and road networks demonstrate the effectiveness and efficiency of the proposed solution.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Computer science and engineering
dc.titleAn efficient algorithm for mapping vehicle trajectories onto road networksen_US
dc.typeConference Paper
dc.contributor.conferenceInternational Conference on Advances in Geographic Information Systems (20th : 2012)en_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1145/2424321.2424427


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