D. Patel, M. Jalayer, N. Carla Bouaynaya
Rowan University,
United States
Keywords: traffic video analytics tool, interaction safety, surrogate safety measures
Summary:
In recent years, identifying road users' behavior and conflicts at intersections has become an essential data source for evaluating traffic safety. According to the Federal Highway Administration (FHWA) state in 2020, more than 50% of fatal and injury crashes occurred at or near the intersections. In addition, millions of minor crashes and conflicts are not reported every year due to their lower level of intensity. This increase in the crash fatality rate and unidentified traffic conflicts have raised concerns for the safety of road users at the intersection. This study developed an innovative artificial intelligence (AI)-based video analytic tool to assess intersection safety using surrogate safety measures. Surrogate safety measures (e.g., Post-encroachment Time (PET) and Time-to-Collision (TTC)) are extensively used to identify future threats, such as rear-end and left-turning collisions due to vehicle and road users' interactions. To extract the trajectory data, this project integrates a real-time AI detection model - YOLO-v5 with a tracking framework based on the DeepSORT algorithm. 54 hours of high-resolution video data were collected from a six-signalized intersection in Glassboro, New Jersey. Non-compliance behaviors, such as red-light running and pedestrian jaywalking, are captured to better understand the risky behaviors at intersections. The proposed approach achieved an accuracy between 95% to 98% for detecting and tracking the road users' trajectories. Additionally, a user-friendly web-based application has been developed, that provides direction-based vehicle volume, vehicles running a red light, PET and TTC for both vehicle-to-vehicle and vehicle-to-pedestrian conflicts, pedestrian volume, and pedestrian jaywalking events. Overall, the developed tool will provide valuable information for engineers and policymakers to develop and implement effective countermeasures to enhance intersection safety.