Crash severity prediction models enable different agencies to predict the severity of a
reported crash with unknown severity or the severity of crashes that may be expected to …

The single-vehicle crash has been recognized as a critical crash type due to its high fatality
rate. In this study, a two-year crash dataset including all single-vehicle crashes in New …

The current study undertakes a unique research effort to quantify the impact of various
exogenous factors on crash severity over time. Specifically, we examine if over time, the …

Traffic crashes impose tremendous socio-economic losses on societies. To alleviate these
concerns, countless traffic safety researches have shed light on the cognition of observable …

This study examines contributing variables affecting the driver injury-severity in single-
vehicle roadway departure crashes. To capture the threshold heterogeneity and unobserved …

Macroscopic traffic crash analyses have been conducted to incorporate traffic safety into
long-term transportation planning. This study aims at developing a multivariate Poisson …

In the transportation safety field, in an effort to improve safety, statistical models are
developed to identify factors that contribute to crashes as well as those that affect injury …

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

Crash severity has been extensively studied and numerous methods have been developed
for investigating the relationship between crash outcome and explanatory variables. Crash …

Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the
vehicle crash severity as it does not require the assumption of normality, linearity, or …