Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14591
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dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorWang, J-
dc.creatorSumalee, A-
dc.date.accessioned2015-10-13T08:27:55Z-
dc.date.available2015-10-13T08:27:55Z-
dc.identifier.issn1024-123Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/14591-
dc.language.isoenen_US
dc.publisherHindawi Publishing Corporationen_US
dc.rightsCopyright © 2015 Jiankai Wang and Agachai Sumalee. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following article: Wang, J., & Sumalee, A. (2015). Automatic freeway incident detection for free flow conditions: a vehicle reidentification based approach using image data from sparsely distributed video cameras. Mathematical Problems in Engineering, 2015, is available at https//doi.org/10.1155/2015/102380en_US
dc.titleAutomatic Freeway Incident Detection for Free Flow Conditions: A Vehicle Reidentification Based Approach Using Image Data from Sparsely Distributed Video Camerasen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2015en_US
dc.identifier.doi10.1155/2015/102380en_US
dcterms.abstractThis paper proposes a vehicle reidentification (VRI) based automatic incident algorithm (AID) for freeway system under free flow condition. An enhanced vehicle feature matching technique is adopted in the VRI component of the proposed system. In this study, arrival time interval, which is estimated based on the historical database, is introduced into the VRI component to improve the matching accuracy and reduce the incident detection time. Also, a screening method, which is based on the ratios of the matching probabilities, is introduced to the VRI component to further reduce false alarm rate. The proposed AID algorithm is tested on a 3.6 km segment of a closed freeway system in Bangkok, Thailand. The results show that in terms of incident detection time, the proposed AID algorithm outperforms the traditional vehicle count approach.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMathematical problems in engineering, 2015, v. 2015, 102380-
dcterms.isPartOfMathematical problems in engineering-
dcterms.issued2015-
dc.identifier.scopus2-s2.0-84937779847-
dc.identifier.eissn1563-5147en_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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