Enhancing Utah's Rest Area Safety Through AI-Based Near-Miss Detection and Risk Mapping
State-maintained rest areas are facing increasing safety risks as infrastructure ages and traveler demand grows, raising concerns about both user well-being and operational efficiency. Utilizing open-source data and video from surveillance cameras in rest areas managed by the Utah Department of Transportation (UDOT), this project proposes to incorporate a safety-focused analysis layer into rest area management in Utah. The research team will develop computer vision pipelines for multi-object tracking and scene calibration to extract vehicle and pedestrian precise trajectories and speeds, then calculate surrogate safety measures to identify near-miss interactions in parking areas and walkways. These metrics will be integrated into spatiotemporal hotspot maps and a site-level Safety Performance Index (SPI) that ranks locations and time periods with the highest safety risks. The SPI will guide a risk-based shortlist of targeted countermeasures, including signage enhancements, speed-calming features, bollards, and lighting upgrades, each accompanied by projected risk reduction and cost estimates to support informed decision-making.
Language
- English
Project
- Status: Active
- Funding: $110,000.00
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Contract Numbers:
69A3552348308
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Center for Transformative Infrastructure Preservation and Sustainability
North Dakota State University
Fargo, North Dakota United States 58108-6050 -
Project Managers:
Tolliver, Denver
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Performing Organizations:
Department of Civil and Environmental Engineering
110 Central Campus Drive Suite 2000
Salt Lake City, UT United States 84112 -
Principal Investigators:
Rashidi, Abbas
- Start Date: 20251213
- Expected Completion Date: 20271212
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Source Data: CTIPS-064
Subject/Index Terms
- TRT Terms: Artificial intelligence; Countermeasures; High risk locations; Near crashes; Risk assessment; Roadside rest areas; Traffic safety
- Geographic Terms: Utah
- Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 01980785
- Record Type: Research project
- Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
- Contract Numbers: 69A3552348308
- Files: UTC, RIP
- Created Date: Feb 22 2026 10:38AM