Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/14591
| Title: | Automatic Freeway Incident Detection for Free Flow Conditions: A Vehicle Reidentification Based Approach Using Image Data from Sparsely Distributed Video Cameras | Authors: | Wang, J Sumalee, A |
Issue Date: | 2015 | Source: | Mathematical problems in engineering, 2015, v. 2015, 102380 | Abstract: | This 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. | Publisher: | Hindawi Publishing Corporation | Journal: | Mathematical problems in engineering | ISSN: | 1024-123X | EISSN: | 1563-5147 | DOI: | 10.1155/2015/102380 | Rights: | Copyright © 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. The 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/10.1155/2015/102380 |
| Appears in Collections: | Journal/Magazine Article |
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|---|---|---|---|---|
| Wang_Automatic_Freeway_Incident.pdf | 4.64 MB | Adobe PDF | View/Open |
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