Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

Owing to the proximity of the ear canal to the central nervous system, in-ear
electrophysiological systems can be used to unobtrusively monitor brain states. Here, by …

Driver distraction has become a significant cause of severe traffic accidents over the past
decade. Despite the growing development of vision-driven driver monitoring systems, the …

Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …

Driver fatigue detection systems have potential to improve road safety by preventing crashes
and saving lives. Conventional driver monitoring systems based on driving performance and …

The objective measurement of fatigue is of critical relevance in areas such as occupational
health and safety as fatigue impairs cognitive and motor performance, thus reducing …

Facial expression recognition (FER) is an emerging and multifaceted research topic.
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …

The occurrence of mental fatigue during tasks like driving a vehicle increases risk of injury or
death. Changes in electroencephalographic (EEG) activity associated with mental fatigue …

Driver inattention and distraction are the main causes of road accidents, many of which
result in fatalities. To reduce road accidents, the development of information systems to …