For a decade, researchers working in the area of road safety have started exploring the use
of driving behavior data for a better understanding of the causes related to road accidents. A …

The state of practice of investigating traffic safety and operation is primarily based on
traditional data sources, such as spot sensors, loop detectors, and historical crash data …

Future roadways will have a mix of autonomous and automated vehicles with regular
vehicles that require human operators. To ensure the safety of all the road users in such a …

Introduction This study investigates how speed limits affect driver speed selection, as well as
the related crash risk, while controlling for various confounding factors such as traffic …

Effective shared autonomy requires a clear understanding of driver's behavior, which is
governed by multiple psychophysiological and environmental variables. Disentangling this …

Driving on horizontal, curved roads requires much research attention because it tends to
result in more accidents compared to driving on straight roads. Several studies have found …

The increasing accessibility of mobility datasets has enabled research in green mobility,
road safety, vehicular automation, and transportation planning and optimization. Many …

Road crashes continue to be a leading cause of death globally, with most of these crashes
reportedly occurring due to human factors. Traditional road safety assessment utilises …

The severity of roadway departure crashes mainly depends on the roadside features,
including the sideslope, fixed-object density, offset from fixed objects, and shoulder width …

Considering the role of behavioral and environmental factors on road accidents and traffic
intensities, the characterization of vehicle use and driver behavior opens new opportunities …