Reducing the severity of injuries resulting from motor-vehicle crashes has long been a
primary emphasis of highway agencies and motor-vehicle manufacturers. While progress …

Traffic accidents are one main cause of human fatalities in modern society. With the fast
development of connected and autonomous vehicles (CAVs), there comes both challenges …

The analysis of highway-crash data has long been used as a basis for influencing highway
and vehicle designs, as well as directing and implementing a wide variety of regulatory …

This research develops a mixed logit model of driver-injury severity in single-vehicle crashes
in California. The research especially considers the heterogeneous effects of age and …

This study seeks to identify and analyze variations in the effect of contributing factors on
injury severities of single-vehicle accidents across various lighting and weather conditions …

This research explores the factors contributing to the injury severity of bicyclists in bicycle–
motor vehicle accidents using a multinomial logit model. The model predicts the probability …

Rear-end crash is one of the most common types of traffic crashes in the US A good
understanding of its characteristics and contributing factors is of practical importance …

To explore the factors contributing to driver injury severity in traffic accidents, parametric
regression models, such as multinomial logit models (MNLs) or ordered probabilistic …

This paper formulates and estimates an econometric model, referred to as the latent
segmentation based generalized ordered logit (LSGOL) model, for examining driver injury …

Crashes occurring on rural two-lane highways are more likely to result in severe driver
incapacitating injuries and fatalities. In this study, mixed logit models are developed to …