BACKGROUND: Traditional crash prediction models, such as generalized linear regression
model, are incapable of taking into account multilevel data structure. Therefore they suffer …

This study presents multi-level analyses for single-and multi-vehicle crashes on a
mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were …

Road crashes have an unquestionably hierarchical crash-car-occupant structure. Multilevel
models are used with correlated data, but their application to crash data can be difficult. The …

An important problem in road traffic accident research is the resolution of the magnitude by
which individual accident characteristics affect the risk of fatality for each person involved …

Traditional hierarchical modeling has been proposed to account for unobserved
heterogeneity in the crash analysis. Previous studies investigated the grouping of individual …

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

Safety and efficiency are commonly regarded as two significant performance indicators of
transportation systems. In practice, road network planning has focused on road capacity and …

It is important to examine the nature of the relationships between roadway, environmental,
and traffic factors and motor vehicle crashes, with the aim to improve the collective …

Road traffic crashes threaten thousands of drivers every day and significant efforts have
been put forth to reduce the number and mitigate the impacts of traffic crashes. Although the …

Traffic crashes are more likely to occur at intersections where the traffic environment is
complicated. In this study, a hybrid approach combining cluster analysis and hierarchical …