A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …

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 …

This study aims to compare the accident injury severity of e-bikes with that of other types of
two-wheelers based on accident data and to analyze the factors influencing them. Using …

The fatal accidents on the roads remain a global concern. Daily, approximately 18 traffic
accidents occur in the Peninsular Malaysia that cause on an average one death in every …

Predicting crash injury severity is a crucial constituent of reducing the consequences of
traffic crashes. This study developed machine learning (ML) models to predict crash injury …

This study presents an effort to investigate the determinants of driver injury severity in run-off-
road (ROR) crashes. In order to account for unobserved heterogeneity, a random parameter …

This document defines a taxonomy of basic terms used in the description of an Operational
Design Domain (ODD) for an Automated Driving System (ADS). Among others, the …

To undertake a reliable analysis of injury severity in road traffic accidents, a complete
understanding of important attributes is essential. As a result of the shift from traditional …

Many people lose their lives in road accidents because they do not receive timely treatment
after the accident from emergency medical services; providing timely emergency services …

The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at
signalized intersections under the mixed traffic environment in Changsha, China. For this …