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 …

Scenario-based testing for the safety validation of highly automated vehicles is a promising
approach that is being examined in research and industry. This approach heavily relies on …

One of the major challenges that autonomous cars are facing today is driving in urban
environments. To make it a reality, autonomous vehicles require the ability to communicate …

The process of verification and validation of automated vehicles poses a multi-faceted
challenge with far-reaching societal, economical and ethical consequences. In particular …

This paper presents a study that aimed to identify the importance of eye contact and
gestures between pedestrians and drivers. A video-based observation and coding was …

“A grave problem that developed in New Hampshire… now has all the motor-vehicle
commissioners of the eastern states in a wax. It's whether radios should be allowed on cars …

Distracted driver classification (DDC) plays an important role in ensuring driving safety.
Although many datasets are introduced to support the study of DDC, most of them are small …

The naturalistic driving study (NDS) is an innovative research method characterized by the
continuous recording of driving information using advanced instrumentation under real …

Driver behavior profiling has been gaining increased attention due to its relevance in many
applications. For instance, car insurance telematics and fleet management entities have …