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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/30160

Title: Validation of Road Safety Surrogate Measures as a Predictor of Crash Frequency Rates on a Large-scale Microsimulation Network
Authors: Ariza, Alexander
Advisor: Shalaby, Amer Saïd
Persaud, Bhagwant
Department: Civil Engineering
Keywords: traffic conflict
microsimulation
crash frequency
road safety
SSAM
Issue Date: 1-Dec-2011
Abstract: 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.
URI: http://hdl.handle.net/1807/30160
Appears in Collections:Master

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