Highway user-rail crashes have a significant effect on highway user safety rating. However, very little attention is garnished on the subject. An understanding of the factors contributing to the levels of injury severity is an important step toward making the transportation system safer and more reliable. The main goal of this thesis is to explore the impact of various factors involved in highway user crashes on Highway-Rail at Grade Crossings (HRGCs) and provide appropriate mitigation measures. The logistic regression modeling approach (specifically ordered and unordered logit models) was applied to predict the three levels of highway user crash severity on HRGC as a function of various factors involved. A comparison was also performed between the two logit models. The explanatory variables were obtained from the USDOT crossing inventory and HRGCs crash data. The study revealed that some variables such as type of crash circumstance type, pedestrian gender, adverse weather condition, train speed, vehicle speed, HRGC surface type, traffic volume and number of traffic lanes were found to be statistically significant factors contributing to highway user crashes on HRGC. In addition, ordered logit model were identified to be better in estimating the highway user crash severity level on HRGCs.

Date of publication

Fall 1-21-2014

Document Type




Persistent identifier