Estimation of Traffic Conflicts at Signalized Intersections Using High-Resolution Traffic Signal Data

Principal Investigator:

Gary Davis, Professor, Civil, Environmental and Geo-Engineering

Co-Investigator

  • Henry Liu, Associate Professor, Civil, Environmental and Geo-Engineering

Project Summary:

This project explored the possibility of using high-resolution traffic signal data to evaluate intersection safety. Traditional methods using historical crash data collected from infrequently and randomly occurring vehicle collisions can require several years to identify potentially risky situations. By contrast, this method estimates potential traffic conflicts using high-resolution traffic signal data collected from the SMART-Signal system. The potential conflicts estimated in this research include both red-light running events, when stop-bar detectors are available, and crossing (i.e. right-angle) conflicts. Preliminary testing based on limited data showed that estimated conflict frequencies were better than AADT for predicting frequencies of angle crashes. With additional validation this could provide a low-cost and easy-to-use tool for traffic engineers to evaluate traffic safety performance at signalized intersections.

Sponsor:

Project Details: