Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …

One critical bottleneck that impedes the development and deployment of autonomous
vehicles is the prohibitively high economic and time costs required to validate their safety in …

This paper reviews the history of automotive technology development and human factors
research, largely by decade, since the inception of the automobile. The human factors …

Automated vehicles (AVs) must be thoroughly evaluated before their release and
deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N …

The safety of automated vehicles (AVs) must be assured before their release and
deployment. The current approach to evaluation relies primarily on 1) testing AVs on public …

Presently, the collection and analysis of naturalistic data is the most credited method for
understanding road user behavior and improving traffic safety. Such methodology was …

In Europe, the use of electric bicycles is rapidly increasing. This trend raises important safety
concerns: Is their use compatible with existing infrastructure and regulations? Do they …

Automated Driving Systems (ADS) require extensive evaluation to assure acceptable levels
of safety before they can operate in real-world traffic. Although many tools are available to …

Big data has shown its uniquely powerful ability to reveal, model, and understand driver
behaviors. The amount of data affects the experiment cost and conclusions in the analysis …

This paper investigates the problem of driver distraction detection using driving performance
indicators from onboard kinematic measurements. First, naturalistic driving data from the …