Traffic crashes cause a lot of fatality and injuries every year. Robust and reliable driver
monitoring system is an important step toward achieving higher vehicle autonomy level, as …

Automated vehicles (AV) have the potential to decrease driving-related accidents and traffic
congestion and to reduce fuel consumption and carbon emissions. However, because of a …

This study investigated how driver discomfort was influenced by different types of automated
vehicle (AV) controllers, compared to manual driving, and whether this response changed in …

Driving simulation is an efficient, safe, and data‐collection‐friendly method to examine
driving behavior in a controlled environment. However, the validity of a driving simulator is …

Simulator training is becoming increasingly important for training of time-critical and dynamic
situations. Hence, how simulator training in such domains is planned, carried out and …

More than 1.3 million people lose their lives every year in traffic accidents. Improving road
safety requires designing better vehicles and investigating drivers' abilities more closely …

Highways are one of the most suitable scenarios for automated driving technology. For
conditionally automated driving, drivers are required to take over the vehicle when the …

Motion platforms have been used in simulators of all types for several decades. Since it is
impossible to reproduce the accelerations of a vehicle without limitations through a …

There is a myriad of methodologies to assess driving performance after a stroke. These
include psychometric tests, driving simulation, questionnaires, and/or road tests. Research …

Within the field of Brain Computer Interfacing (BCI), Electroencephalography (EEG) is the
most widely applied modality. But most of the EEG based BCI applications use expensive …