A large proportion of car accidents are caused by distracted drivers. Thus, comprehensive
analysis and understanding on driver distraction is essential for traffic safety improvement …

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend
for the development of daily routine applications. However, in the case of heterogeneous …

Driver cognitive distraction, a critical factor for road safety, is challenging for researchers to
evaluate, especially under real conditions. This paper introduces a novel method for …

In the future, vehicles will be equipped with increasingly advanced interactive intelligent
electronic devices, which will induce drivers to conduct secondary tasks, thereby leading to …

The aim of this study was to analyze and compare the effects of different types of digital
billboard advertisements (DBAs) on drivers' performance and attention allocation. Driver …

Driver distraction is one of the major causes of accidents. Most methods for inferring
distracted driving behaviors are vision-based systems that determine the head's orientation …

The driver's state and behavior are crucial for the driving process, which affect the driving
safety directly or indirectly. Electroencephalography (EEG) signals have the advantage of …

The present study utilizes the significant differences in θ, α, and β band power spectra
observed in electroencephalograms (EEGs) during distracted versus focused driving. Three …

Electroencephalography (EEG) has the potential to measure a person's cognitive state,
however, we still only have limited knowledge about how well-suited EEG is for recognising …

A difficult challenge for today's driver monitoring systems is the detection of cognitive
distraction. The present research presents the development of a theory-driven approach for …