Automatic Freeway Incident Detection for Free Flow Conditions: A Vehicle Reidentification Based Approach Using Image Data from Sparsely Distributed Video Cameras

dc.contributor.authorJiankai Wang
dc.contributor.authorAgachai Sumalee
dc.date.accessioned2025-07-21T05:55:33Z
dc.date.issued2015-01-01
dc.description.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.
dc.identifier.doi10.1155/2015/102380
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/4961
dc.subjectComponent (thermodynamics)
dc.subjectFeature (linguistics)
dc.subjectFalse alarm
dc.subject.classificationVehicle License Plate Recognition
dc.titleAutomatic Freeway Incident Detection for Free Flow Conditions: A Vehicle Reidentification Based Approach Using Image Data from Sparsely Distributed Video Cameras
dc.typeArticle

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