Traffic Safety Analysis of a Signalized T-Intersection Using Surrogate Safety Measures

Surrogate safety measures (SSM) provide a potent tool for real-time traffic safety assessment, capturing extensive data on potential traffic conflicts in short timeframes. However, a research gap exists in analyzing the temporal and spatial distribution of such conflicts at signalized intersections. This study analyzes traffic video data from a signalized T-intersection and proposes an algorithm to identify traffic conflicts using indicators like modified TTC (MTTC) and Crash Index (CI). Additionally, an algorithm is introduced to analyze the temporal and spatial distribution of conflict frequencies during a signal cycle. Results reveal that the highest conflict frequency coincides with the initial 10% of the green light signal time, with the most critical location identified within 10 m upstream of the stop line. These findings offer valuable insights for real-time safety enhancement at signalized intersections.