| The objectives of this study were to explore the development of zonal and arterial level collision prediction models that incorporate characteristics applicable to urban transit planning. A generalized linear modelling approach with a Negative Binomial regression error structure was employed using a dataset from Toronto, Canada. The zonal-level models indicate that vehicle kilometers traveled, bus or streetcar kilometers traveled, arterial road kilometers, bus stop density, stop location, and average posted speed have significant associations with transit-involved collision occurrence. The arterial-level models suggest that AADT, transit frequency, segment length, average stop spacing, presence of on-street parking, and stop locations have significant associations with collisions involving all motor vehicles. It is evident that these models can provide transit agencies with decision-support tools for considering safety implications in the strategic and service planning processes and to predict future levels of transit-involved collisions for an existing and a new transportation network or arterial route. |
