Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis

J Safety Res. 2021 Jun;77:311-323. doi: 10.1016/j.jsr.2021.03.006. Epub 2021 Mar 24.


Introduction: Although stop signs are popular in North America, they have become controversial in cities like Montreal, Canada where they are often installed to reduce vehicular speeds and improve pedestrian safety despite limited evidence demonstrating their effectiveness. The purpose of this study is to evaluate the impact of stop-control configuration (and other features) on safety using statistical models and surrogate measures of safety (SMoS), namely vehicle speed, time-to-collision (TTC), and post-encroachment time (PET), while controlling for features of traffic, geometry, and built environment.

Methods: This project leverages high-resolution user trajectories extracted from video data collected for 100 intersections, 336 approaches, and 130,000 road users in Montreal to develop linear mixed-effects regression models to account for within-site and within-approach correlations. This research proposes the Intersection Exposure Group (IEG) indicator, an original method for classifying microscopic exposure of pedestrians and vehicles.

Results: Stop signs were associated with an average decrease in approach speed of 17.2 km/h and 20.1 km/h, at partially and fully stop-controlled respectively. Cyclist or pedestrian presence also significantly lower vehicle speeds. The proposed IEG measure was shown to successfully distinguish various types of pedestrian-vehicle interactions, allowing for the effect of each interaction type to vary in the model.

Conclusions: The presence of stop signs significantly reduced approach speeds compared to uncontrolled approaches. Though several covariates were significantly related to TTC and PET for vehicle pairs, the models were unable to demonstrate a significant relationship between stop signs and vehicle-pedestrian interactions. Therefore, drawing conclusions regarding pedestrian safety is difficult. Practical Applications: As pedestrian safety is frequently used to justify new stop sign installations, this result has important policy implications. Policies implementing stop signs to reduce pedestrian crashes may be less effective than other interventions. Enforcement and education efforts, along with geometric design considerations, should accompany any changes in traffic control.

Keywords: Computer vision; Pedestrians; Regression models; Stop signs; Surrogate safety; Traffic control.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Built Environment*
  • Canada
  • Cities
  • Environment Design
  • Humans
  • Models, Statistical
  • Motor Vehicles / statistics & numerical data*
  • Pedestrians / statistics & numerical data*
  • Policy
  • Safety