This paper proposes a random-parameter bivariate zero-inflated negative binomial
(RBZINB) regression model for analyzing the effects of investigated variables on crash …

Crash data are collected through police reports and integrated with road inventory data for
further analysis. Integrated police reports and inventory data yield correlated multivariate …

Recent research demonstrates the appropriateness of multivariate regression models in
crash count modelling when one specific type of crash counts needs to be analysed, since …

Objective: Rear-end crashes are a type of road traffic accident that occurs frequently.
Currently, the application of advanced statistical models to predict the frequency of accident …

In order to improve traffic safety, a large amount of works focusing on crash prediction and
identifying factors contributing to crashes. However, the ignorance of data unobserved …

Highways provide the basis for safe and efficient driving. Road geometry plays a critical role
in dynamic driving systems. Contributing factors such as plane, longitudinal alignment, and …

In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency
were taken into consideration for distinguishing between rural and urban road segment …

Crash frequency prediction models have been an important subject of safety research that
unveils a relationship between crash occurrences and their influencing factors. Recently, the …

Urban midblock crashes are influenced mainly by traffic operation and roadway geometric
features. In this paper, 10-year crash data from 1,506 directional urban midblock segments …

Given the enormous losses to society resulting from large truck involved crashes, a
comprehensive understanding of the effects of highway geometric design features on the …