Using Macrolevel Collision Prediction Models in Road Safety Planning Applications

Abstract

This paper describes the use of several recently developed macrolevel collision prediction models (CPMs) in two road safety planning applications. Data from several urban neighborhoods in the Greater Vancouver Regional District (GVRD) in the province of British Columbia, Canada, were used to present and test model-use guidelines in two road safety planning applications. In the first case study, an areawide traffic calming collision modification factor was estimated for GVRD urban areas, for “total” and “severe” collisions, to be in the range of –0.40 and –0.39, respectively. In the second case study, four neighborhood network structures were evaluated, and two test networks that appeared safer than conventional grid and cul-de-sac neighborhood street patterns were revealed, mostly because of the increased use of three-way intersections. Moreover, cul-de-sac networks appeared to be much safer than grid networks, by nearly three to one. The results suggested that the models and model-use guidelines could complement and enhance traditional road safety improvement programs and could provide new and improved empirical tools for planners and engineers to do road safety planning. It is hoped that development of guidelines for macrolevel CPM use will facilitate improved decisions by community planners and engineers and, ultimately, neighborhood traffic safety for residents and other road users.