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 …

In recent years, road traffic accidents, as a leading cause of accidental deaths, have been
attracting more and more attention across several disciplines. Notably, the feature study on …

Motorcycle road traffic accidents represent a big concern, as vulnerable road users account
for more than half of all road deaths worldwide. The estimation of the influential factors …

Providing accurate prediction of the severity of traffic collisions is vital to improve the
efficiency of emergencies and reduce casualties, accordingly improving traffic safety and …

Accidents typically occurred on roads, resulting in significant societal losses. Road accidents
are a worldwide issue that result in the loss of precious human lives and property. The …

Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key
topic of research in road traffic safety. The current study analyzed the driver injury severity …

Examining the impacts of accident characteristics and differentiated built environment factors
on accident severity at inherent accident hotspots within cities can help managers to adjust …

This study planned to predict and analyze the driver injury severity (DIS) using 12 machine
learning (ML) algorithms. Police reports of single-and two-vehicle accidents that occurred …

Predicting accident severity using data analysis and machine learning is vital for enhancing
road safety, as this data can help policymakers and law enforcement gain insights into …

The road traffic accidents data represents an important source of knowledge interesting for
various decision processes. Based on the target group of users, we can identify several …