United States Department of Transportation
i
Track Intrusion Detection and Track Integrity Evaluation
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2024-09-30
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[PDF-955.10 KB]
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Edition:June 1, 2023 – August 31, 2024
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Abstract:Track intrusion, particularly trespassing within railroad rights-of-way, poses a major safety risk, leading to more fatalities than train-vehicle collisions. This research introduces a Hybrid Region-based Convolutional Network (Hybrid-RCNN) that integrates foreground segmentation and object detection to enhance surveillance at rail crossings. The model performs multiple tasks, including object detection, classification, and tracking, to efficiently monitor unauthorized activities. Testing shows the Hybrid-RCNN's superior accuracy compared to models like Mask-RCNN, highlighting its potential to improve railway safety by identifying and mitigating hazards more effectively.
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