The paper presents a comparison between two modeling techniques, Bayesian network and
Regression models, by employing them in accident severity analysis. Three severity …

INTRODUCTION: This study describes a method for reducing the number of variables
frequently considered in modeling the severity of traffic accidents. The method's efficiency is …

Introduction: Traffic crashes could result in severe outcomes such as injuries and deaths.
Thus, understanding factors associated with crash severity is of practical importance. Few …

Based on an overall consideration of factors affecting road safety evaluations, the Bayesian
network theory based on probability risk analysis was applied to the causation analysis of …

Traffic accidents are still the main cause of fatalities, injuries and significant delays in
highways. Understanding the accident contributing factor is imperative to increase safety in …

The purpose of this study is to minimize the negative influences of the severe traffic
accidents in China by profoundly analyzing the complex coupling relations among accident …

This paper presents a model system to predict severity and duration of traffic accidents by
employing Ordered Probit model and Hazard model, respectively. The models are estimated …

Traffic accidents are costing the world more than a million lives yearly alongside monetary
losses, especially in the Gulf Cooperation Council region. This situation raised the need to …

This study describes crash causes, conditions, and distribution of accident hot spots along
with an analysis of the risk factors that significantly affect severity levels of crashes and their …

In spite of significant advances in highways safety, a lot of crashes in high severities still
occur in highways. Investigation of influential factors on crashes enables engineers to carry …