Our objectives were to assess the efficacy of active inference models for capturing driver takeovers from automated vehicles and to evaluate the links between model parameters and self-reported cognitive fatigue, trust, and situation awareness.

The study investigates users' tendency to access decision support (DS) systems as a function of the correlation between the DS information and the information users already have, the ongoing interaction with such systems, and the effect of correlated information on subjective trust.

This study aims to compare the relative sensitivity between scene-independent and scene-dependent eye metrics in assessing trainees' performance in simulated psychomotor tasks.

This study investigated the effects of mass and vertical center-of-mass position of combat items attached to a tactical vest, as well as marksmanship posture on rifle marksmanship performance, postural sway, and perceived workload during a simulated rifle shooting task.

This study compared the effects of prior cognitive, physical, and concurrent exertion on physical performance.

The current study investigated the factors that predict drowsy drivers' decisions regarding whether to take breaks versus continue driving during long simulator drives.

To review and synthesise research on technological debiasing strategies across domains, present a novel distributed cognition-based classification system, and discuss theoretical implications for the field.

This study investigated the relationship between human team member contextual control and team performance under time constraints.

The present study investigated how pupil size and heart rate variability (HRV) can contribute to the prediction of operator performance. We illustrate how focusing on mental effort as the conceptual link between physiological measures and task performance can align relevant empirical findings across research domains.

This study aims to investigate the causes of take-over failures in conditional automated driving with spatial-temporal analysis of brain zone activation.

We aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.

We investigate the impact of event uncertainty, decision support (DS) display format, and DS sensitivity on participants' behavior, performance, subjective workload, and perception of DS usefulness and performance in a classification task.

This study examines the extent to which cybersecurity attacks on autonomous vehicles (AVs) affect human trust dynamics and driver behavior.

Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.

The goal of this study was to assess how different real-time gaze sharing visualization techniques affect eye tracking metrics, workload, team situation awareness (TSA), and team performance.

We investigated how people used cues to make Judgments of Difficulty (JODs) while observing automation perform a task and when performing this task themselves.

We investigated how different deceleration intentions (i.e. an automated vehicle either decelerated for leading traffic or yielded for pedestrians) and a novel (Slow Pulsing Light Band - SPLB) or familiar (Flashing Headlights - FH) external Human Machine Interface (eHMI) informed pedestrians' crossing behaviour.

We investigated the impact of low-tempo, repetitive hand movements on vibrotactile sensitivity by employing various temporal and spatial patterns in the hand and wrist area.

To examine the impact of secondary task performance on contextual blindness arising from the suppression and masking of temporal and spatial sequence learning.

An up-to-date and thorough literature review is needed to identify factors that influence driver situation awareness (SA) during control transitions in conditionally automated vehicles (AV). This review also aims to ascertain SA components required for takeovers, aiding in the design and evaluation of human-vehicle interfaces (HVIs) and the selection of SA assessment methodologies.

This study investigated the effects of four takeover request (TOR) times and seven warning modalities on performance and trust in automated driving on a mildly congested urban road scenario, as well as the relationship between takeover performance and trust.