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 …

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 …

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 …

In this paper, an artificial neural network (ANN) was used to predict the injury severity of
traffic accidents based on 5973 traffic accident records occurred in Abu Dhabi over a 6‐year …

A Decision Tree (DT) is a potential method for studying traffic accident severity. One of its
main advantages is that Decision Rules (DRs) can be extracted from its structure. And these …

One of the principal objectives of traffic accident analyses is to identify key factors that affect
the severity of an accident. However, with the presence of heterogeneity in the raw data …

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

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 …

This study uses highway accident data collected in the State of Washington, between 2011
and 2013, to study the factors that affect accident injury-severities. To account for the fixed …

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 …