Intelligent Camera Aided Railway Emergency System (i-CARES)
The highway-railroad grade crossings are a hot spot in terms of vehicle-train collisions. The unexpected crossing blockage not only brings traffic congestion but also raises serious safety concerns for commuters. Previous researchers have already investigated the accident loss and frequency of the accidents around the crossing areas. However, there is no dedicated research to facilitate the information exchange between the railroad and street traffic. In this study, researchers at the University of South Carolina initiated the effort of evaluating traffic conditions at the grade crossings and establish two-way communication between the railroad and street traffic to assist the railroad and drivers in their decision making. A customized detection and tracking algorithm based on deep learning was developed. Results presented in this report indicate the traffic during and after the crossing blockage does follow a pattern.
- Record URL:
- Summary URL:
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
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Corporate Authors:
University of South Carolina, Columbia
Columbia, SC United States 29208Center for Connected Multimodal Mobility
Clemson University
Clemson, SC United States 29634Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Qian, Yu
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0000-0001-8543-2774
- Wang, Yi
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0000-0002-5750-3181
- Rizos, Dimitris
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0000-0001-5764-7911
- Publication Date: 2021-2
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Figures; Photos; References; Tables;
- Pagination: 32p
Subject/Index Terms
- TRT Terms: Cameras; Machine learning; Railroad grade crossings; Traffic surveillance; Vehicle detectors; Wireless communication systems
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Railroads;
Filing Info
- Accession Number: 01839134
- Record Type: Publication
- Contract Numbers: 69A3551747117
- Files: UTC, TRIS, ATRI, USDOT
- Created Date: Mar 22 2022 9:45AM