Using Micro-simulated Traffic Conflicts as a Surrogate Safety Assessment Technique for Evaluating Safety Performance of Transit Design Alternatives at Signalized Intersections

This study focuses on crash prediction modelling at intersection-level using micro-simulation to produce an effective surrogate safety assessment measure. The developed crash prediction model followed generalized linear model with negative binomial error structure to correlate the simulated traffic conflicts with the observed crash frequency in Toronto, Ontario, Canada. Individual crash prediction models were developed for every impact types and for transit-involved crash type. The resulting statistical performance suggested adequate predictive ability. Based on the established correlation between the simulated conflicts and observed crashes, scenarios were developed to investigate the safety impacts of transit infrastructures by making hypothetical transit infrastructure modifications in the micro-simulation networks. The findings implied that the existing transit signal priority schemes implemented in Toronto had negative contributions on safety performance and that the existing near-sided stop positioning and streetcar transit type were safer at their existing states than if they were replaced by their respective counterparts.