Introduction: Scholarly research on road accidents over the past 50 years has generated
substantial literature. We propose a robust search strategy to retrieve and analyze this …

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

As mobile device location data become increasingly available, new analyses are revealing
the significant changes of mobility pattern when an unplanned event happened. With …

Distracted driving has been considered one of the main reasons for traffic crashes in recent
times, especially among young drivers. The objectives of this study were to identify the …

This study investigates the inclusion of spatio-temporal correlation and interaction in a
multivariate random-parameters Tobit model and their influence on fitting areal crash rates …

A new distribution defined on (0, 1) interval is introduced. Its probability density and
cumulative distribution functions have simple forms. Thanks to its simple forms, the …

Introduction: It has been demonstrated that weather conditions have significant impacts on
freeway safety. However, when employing an econometric model to examine freeway crash …

Analyzing speed mean and variance is vital to safety management in urban roadway
networks. However, modeling speed mean and variance on structured roads could be …

Predicting pedestrian crashes on urban roads is one of the most important issues related to
urban traffic safety. Due to the lack of spatial correlation and instability in the crash data, the …

Background Although numerous efforts have been devoted to exploring the effects of area-
wide factors on the frequency of pedestrian crashes in neighborhoods over the past two …