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 …

Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and developing effective road safety …

Driving style may have an important effect on traffic safety. Proactive crash risk prediction for
lane-changing behaviors incorporating individual driving styles can help drivers make safe …

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 …

Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …

Motorcycles and motorcyclists have a variety of attributes that have been found to be a
potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road …

Road crashes cost over a million lives each year. Consequently, researchers and transport
engineers continue their efforts to improve road safety and minimize road crashes. With the …

In road safety, real-time crash prediction may play a crucial role in preventing such traffic
events. However, much of the research in this line generally uses data aggregated every five …

Traffic accidents are one of the most important concerns of the world, since they result in
numerous casualties, injuries, and fatalities each year, as well as significant economic …

Due to the difficulty of obtaining traffic flow data and conflicts simultaneously, conflict-based
analysis using macroscopic traffic features is much less studied. This research aims to …