Proactive Safety Analysis of Urban Intersections Using the Traffic Conflict Technique and SSAM Approach: A Case Study in Tashkent City.

Abstract

The development of sustainable and safe communities requires a strong emphasis on traffic safety. This study aims to improve intersection safety in urban areas using surrogate safety analysis. Traditional crash-based assessments face challenges due to the infrequency of accidents and difficulties in accurate data collection. To overcome these limitations, the Surrogate Safety Assessment Model (SSAM) is applied, utilizing conflict indicators such as Time to Collision (TTC) and Post-Encroachment Time (PET) to estimate potential safety risks. This study implements the Traffic Conflict Technique (TCT) at multiple signalized intersections along a busy city street in Tashkent, Uzbekistan. By integrating VISSIM simulation models with SSAM, the research evaluates traffic flow and conflict patterns at critical intersections. The study demonstrates a strong correlation between serious conflicts and actual crash occurrences, reinforcing the predictive reliability of conflict-based safety assessments. This simulation-driven approach provides data-driven insights to support proactive safety planning in rapidly growing urban areas.