Show simple item record

dc.contributor.authorAslam, Javed
dc.contributor.authorLim, Sejoon
dc.contributor.authorPan, Xinghao
dc.contributor.authorRus, Daniela L.
dc.date.accessioned2014-10-07T19:58:11Z
dc.date.available2014-10-07T19:58:11Z
dc.date.issued2012-11
dc.identifier.isbn9781450311694
dc.identifier.urihttp://hdl.handle.net/1721.1/90617
dc.description.abstractTraffic congestion, volumes, origins, destinations, routes, and other road-network performance metrics are typically collected through survey data or via static sensors such as traffic cameras and loop detectors. This information is often out-of-date, difficult to collect and aggregate, difficult to analyze and quantify, or all of the above. In this paper we conduct a case study that demonstrates that it is possible to accurately infer traffic volume through data collected from a roving sensor network of taxi probes that log their locations and speeds at regular intervals. Our model and inference procedures can be used to analyze traffic patterns and conditions from historical data, as well as to infer current patterns and conditions from data collected in real-time. As such, our techniques provide a powerful new sensor network approach for traffic visualization, analysis, and urban planning.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CPS-0931550)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 0735953)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-09-1-105)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-09-1-1031)en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2426656.2426671en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleCity-scale traffic estimation from a roving sensor networken_US
dc.typeArticleen_US
dc.identifier.citationJaved Aslam, Sejoon Lim, Xinghao Pan, and Daniela Rus. 2012. City-scale traffic estimation from a roving sensor network. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (SenSys '12). ACM, New York, NY, USA, 141-154.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. School of Engineeringen_US
dc.contributor.mitauthorLim, Sejoonen_US
dc.contributor.mitauthorRus, Daniela L.en_US
dc.relation.journalProceedings of the 10th ACM Conference on Embedded Network Sensor Systems (SenSys '12)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsAslam, Javed; Lim, Sejoon; Pan, Xinghao; Rus, Danielaen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5473-3566
mit.licenseOPEN_ACCESS_POLICYen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record