A study was done to explore the suitability of intersection and arterial collision prediction models based on traffic conflicts, generated using the Paramics microsimulation suite and the Surrogate Safety Assessment Model (SSAM). A linear regression model and a generalized linear model with a negative binomial error structure were explored to correlate conflicts to crash rates, as well as the conflict-based models suggested by SSAM. The model predictions were compared to volume-based predictions and historical data from Toronto, Ontario, Canada. The volume- based predictions were calculated using a negative binomial generalized linear model, fitted to the same arterial and intersection sets used to fit the conflict-based models. The results show the predictions generated by a conflict-based model were comparable for intersections, but poor for arterials.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/30160 |
| Date | 01 December 2011 |
| Creators | Ariza, Alexander |
| Contributors | Shalaby, Amer Saïd, Persaud, Bhagwant |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.002 seconds