Multinomial logit (MNL) models have been applied extensively in the fields of transportation engineering, marketing and recreational demand modeling. So far, this type of model has not been used to estimate the proportionof crashes by collision type. Consequently, the objective of this study consists of investigating the applicability of MNL models for predicting the proportion of crashes by collision type and their use in estimation of crash counts by collision type. This method is compared with two other methods described in recent publications for estimation of crash counts by collision type: 1) estimated using fixed proportions of crash counts for all collision types; 2) estimated using collision type models. To accomplish the study objective, crash data collected from 2002-2006 on rural two-lane undivided highway segments in Minnesota were employed. The results of thisstudy show that the MNL model can be used for predicting the proportion of crashes by collision type, at least for the dataset used in this study. Furthermore, the method based on the MNL model was found useful in estimation of crash counts by collision type and it performed better than the method based on the use of fixed proportions. However, using collision type models was still found to be the best method for estimation of crash countsby specific collision type. In cases where collision type models are affected by the small sample size and low sample mean problem, the method based on MNL model is therefore recommended.
Abstract