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Title: Artificial Intelligence–Aided Automated Detection of Railroad Trespassing
Accession Number: 01713983
Record Type: Component
Availability: Find a library where document is available Abstract: Large volumes of surveillance video data deployed in the railroad industry open many possibilities for detecting and preventing unsafe trespassing on railroad tracks. Monitoring these data, however, is highly time- and resource-consuming. In this article, authors describe an artificial intelligence (AI) algorithm that automatically detects trespassing events in real time. The system was tested on two different safety-critical scenarios: a grade crossing in Ashland, Virginia and two right-of-ways (ROWs) in Thomasville, North Carolina. The AI system was able to accurately detect trespasses in these locations. With this AI technology, it is possible to compile large data sets of trespassing events and provide useful insights into trespassing behavior to ultimately support risk mitigation decisions.
Language: English
Authors: Zaman, Asim FRen, BaozhangLiu, XiangPagination: pp 30-35
Publication Date: 2019-7
Serial: Media Type: Digital/other
Features: Figures; Photos; References
TRT Terms: Geographic Terms: Subject Areas: Pedestrians and Bicyclists; Railroads; Safety and Human Factors
Files: TRIS, TRB, ATRI
Created Date: Aug 14 2019 9:30AM
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