Project Details

Abstract

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. We 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.

Project Word Files