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 …

Road accidents are one of the most relevant causes of injuries and death worldwide, and
therefore, they constitute a significant field of research on the use of advanced algorithms …

Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine
learning algorithms for predicting crash severity have recently gained interest by the …

Traffic accidents are among the most critical issues facing the world as they cause many
deaths, injuries, and fatalities as well as economic losses every year. Accurate models to …

As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …

Roadway traffic safety is a major concern for transportation governing agencies as well as
ordinary citizens. In order to give safe driving suggestions, careful analysis of roadway traffic …

This study uses classification algorithms to establish models to predict the severity of crash
injuries when motorcycle crashes occur. In this study, the power of multi-layer perceptron …

Crash severity models play a crucial role in evaluating the influencing factors in the severity
of traffic crashes. In this study, Extremely Randomised Tree (ERT) is used as a machine …

Kingdom of Among the G20 countries, Saudi Arabia (KSA) is facing alarming traffic safety
issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been …

This work analyses influence of road, weather and crash-specific factors on crash severity
outcomes for low-speed urban midblock sections and intersections, for day and night time …