Utilizing Artificial Intelligence with Vision-based Systems for Monitoring Trespassing – Best Practices
The primary objective of this project was to evaluate the deployment of artificial intelligence (AI) applications with vision-based systems for monitoring trespassing to improve transit safety. AI is a term that encompasses many functions in different systems. For this project, AI refers to all machine vision, computational algorithms, pattern recognition, and other tools applied to data collected specifically with vision- or video camera-based systems in the application of transit safety. As part of the process, online reviews, coupled with stakeholder interviews and surveys, were conducted to reach findings. The review identified vision-based AI applications, existing relevant standards, and areas for standards development to improve the safe operation of public transportation systems.
- Record URL:
- Record URL:
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Corporate Authors:
University of South Florida, Tampa
Center for Urban Transportation Research
4202 Fowler Avenue
Tampa, FL United States 33620-5373Federal Transit Administration
Office of Research, Demonstration and Innovation
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Authors:
- Kourtellis, Achilleas
- Lin, Pei-Sung
- Keita, Yaye
- Canavan, Shawn
- Menon, Nikhil
- Publication Date: 2023-9
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Appendices; Figures; Photos; References; Tables;
- Pagination: 80p
Subject/Index Terms
- TRT Terms: Artificial intelligence; Machine vision; Monitoring; Transit safety; Trespassers
- Subject Areas: Data and Information Technology; Public Transportation; Safety and Human Factors;
Filing Info
- Accession Number: 01899515
- Record Type: Publication
- Report/Paper Numbers: FTA Report No. 0256
- Files: TRIS, ATRI, USDOT
- Created Date: Nov 17 2023 9:03AM