Driver workload inference is significant for the design of intelligent human–machine
cooperative driving schemes since it allows the systems to alert drivers before potentially …

The rate of human errors would increase as air traffic control officers (ATCOs) lose situation
awareness (SA), which could also be affected by their perceived workloads. Recognising …

With the level of automation increases in vehicles, such as conditional and highly automated
vehicles (AVs), drivers are becoming increasingly out of the control loop, especially in …

Trust calibration poses a significant challenge in the interaction between drivers and
automated vehicles (AVs) in the context of human-automation collaboration. To effectively …

Tesla's Full Self-Driving Beta (FSD) program introduces technology that extends the
operational design domain of standard Autopilot from highways to urban roads. This …

During the operation of the L3 automated driving system, since there is no need to supervise
the vehicle at all times, the driver is often disengaged from the driving task and engages in a …

It is extremely important to ensure a safe takeover transition in conditionally automated
driving. One of the critical factors that quantifies the safe takeover transition is takeover time …

Understanding existing gender differences in the development of computational thinking
skills is increasingly important for gaining valuable insights into bridging the gender gap …

Driving a vehicle in a safe manner is a highly specialized task that depends on the driver's
cognitive ability, skills, attention, fast processing, interpretation of traffic situations and rules …

(AI) and Machine Learning (ML) are set to revolutionize all industries, Intelligent
Transportation Systems (ITS) field is no exception. However, being a safety-critical system …