Validation of the Surrogate Safety Assessment Model for Assessment of Intersection Safety

Abstract

The surrogate safety assessment model (SSAM) is a software application that reads trajectory files generated by microscopic simulation programs and calculates surrogate measures of safety. This approach eliminates the subjectivity associated with the conventional conflict analysis technique and allows assessment of the safety of a facility under a controlled environment before accidents occur. The specific goal of this research was to validate SSAM as a tool for accident prediction at urban intersections. Two methods were used for validation. The first method compared the simulated number of conflicts from the use of SSAM and the predicted number of injury accidents from analytic models in three reference intersection layouts (four-leg priority intersection, four-leg staggered intersection, and single-lane roundabout). The second method compared SSAM results with conflicts observed on site in four real intersections: two priority ones and two roundabouts. The results indicate that, despite some limitations related to the nature of current traffic microsimulation models, SSAM analysis is an extremely promising approach to assessing the safety of new facilities or innovative layouts.