Limitations of crash data and crash-based methods have given rise to the study of alternate
measures of safety that are not predicated on the occurrence of a crash such as traffic …

Introduction: Road traffic crashes represent a major public health concern, so it is of
significant importance to understand the factors associated with the increase of injury …

The analysis of highway accident data is largely dominated by traditional statistical methods
(standard regression-based approaches), advanced statistical methods (such as models …

Highway accidents are complex events that involve a variety of human responses to external
stimuli, as well as complex interactions between the vehicle, roadway features/condition …

Virtually every statistical analysis of highway safety data is predicated on the assumption
that the estimated model parameters are temporally stable. That is, the assumption that the …

Aggressive driving has become a national traffic-safety concern, with increasing congestion
and other stress-inducing factors making it more likely drivers take out their frustrations by …

Random parameters logit models have become an increasingly popular method to
investigate crash-injury severities in recent years. However, there remain potential elements …

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 …

Using the data from large-truck crashes in Los Angeles over an eight-year period (January
1, 2010 to December 31, 2017), the variation in the influence of factors affecting injury …

Relative to safety assessment using data from observed crashes, conflict-based road safety
assessment can potentially provide additional insights into crash causation processes …