Numerous road safety studies have been dedicated to the estimation of crash frequency and
injury severity models. However, previous research has shown that different factors may …

To examine the difference in contributing factors of rear-end crashes of different injury
severity involving different types of vehicles, this paper proposed random-parameters …

In an effort to improve traffic safety, there has been considerable interest in estimating crash
prediction models and identifying factors contributing to crashes. To account for crash …

Traditional accident analysis typically explores non-time-varying (stationary) factors that
affect accident occurrence on roadway segments. However, the impact of time-varying …

Many studies focused on the development of crash prediction models have resulted in
aggregate crash prediction models to quantify the safety effects of geometric, traffic, and …

The growing concern about the possible safety-related impacts of Intelligent Transportation
Systems (ITS) has focused attention on the need to develop new statistical approaches to …

Road crash prediction models are very useful tools in highway safety, given their potential
for determining both the crash frequency occurrence and the degree severity of crashes …

This study develops a Bayesian spatial generalized ordered logit model with conditional
autoregressive priors to examine severity of freeway crashes. Our model can simultaneously …

This study analyzes driver's injury severity in single-and two-vehicle crashes and compares
the effects of explanatory variables among various types of crashes. The study identified …

This article develops a multinomial logit (MNL) model to investigate and identify significant
contributing factors that determine the pedestrian-vehicle crash severity in North Carolina …