Estimation of Crossing Conflict at Signalized Intersection Using High-Resolution Traffic Data
Henry Liu, Gary A Davis, Shengyin Shen, Xuan Di, Indrajit Chatterjee
Report no. MnDOT 2017-08
This project explores 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, the proposed 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.