Two techniques of modelling crash occurrence were investigated. A principal arterial in Central Florida was selected to calibrate the models. The modelling effort involved using both the multiple linear regression and the Poisson regression methodologies. The results illustrated that the Poisson regression approach is superior to the linear regression. The results also showed the significance of the Annual Average Daily Traffic (AADT) and the log of the section's length on the frequency of crashes. Several geometric design variables also affects crash occurrence, including the degree of horizontal curvature, shoulder, median and lanes widths and whether the location of the crash was urban or rural. The results have important implications on developing predictive models of crash occurrence, and in understanding the factors that influence them. (A)
Samenvatting