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A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance
Deep Patel1, Parisa Hosseini1, Mohammad Jalayer2
1Department of Civil and Environmental Engineering, Rowan University, United States.
Accident; Analysis and Prevention
|September 6, 2023
Summary
This study introduces an AI video analysis tool to assess intersection safety by tracking road user behavior and conflicts. It identifies risky actions and estimates crash likelihood, aiding traffic safety improvements.
Area of Science:
- Traffic Engineering
- Artificial Intelligence
- Computer Vision
Background:
- Intersections are critical safety zones, with over 50% of fatal crashes occurring there.
- Understanding road user behavior and conflicts is vital for enhancing traffic safety.
- Existing methods for intersection safety analysis require advanced tools for comprehensive data collection.
Purpose of the Study:
- To develop an AI-powered video analytic tool for assessing intersection safety.
- To utilize surrogate safety measures and identify non-compliance behaviors.
- To estimate potential crash frequency and rank intersections based on safety.
Main Methods:
- Deployed YOLO-v5 and DeepSORT for real-time trajectory detection and tracking.
- Collected 54 hours of video data from six signalized intersections in Glassboro, NJ.
- Applied Extreme Value Theory (EVT) to estimate crash numbers using surrogate safety measures like PET and TTC.
Main Results:
- Achieved 92%-98% accuracy in detecting and tracking road user trajectories.
- Quantified traffic and pedestrian volumes, red-light running, and pedestrian non-compliance.
- Provided critical safety measures (PET, TTC) and ranked intersections by crash severity score.
Conclusions:
- The AI tool effectively assesses intersection safety and identifies risky behaviors.
- Crash estimation using EVT and surrogate safety measures offers valuable insights for traffic engineers.
- The developed ranking system aids in prioritizing safety interventions at high-risk intersections.
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