On investigating drivers' attention allocation during partially-automated driving.

The use of partially-automated systems require drivers to supervise the system functioning and resume manual control whenever necessary. Yet literature on vehicle automation show that drivers may spend more time looking away from the road when the partially-automated system is operational. In this study we answer the question of whether this pattern is a manifestation of inattentional blindness or, more dangerously, it is also accompanied by a greater attentional processing of the driving scene.

On the impact of on-road partially-automated driving on drivers' cognitive workload and attention allocation.

The use of partially-automated or SAE level-2 vehicles is expected to change the role of the human driver from operator to supervisor, which may have an effect on the driver's workload and visual attention. In this study, 30 Ontario drivers operated a vehicle in manual and partially-automated mode. Cognitive workload was measured by means of the Detection Response Task, and visual attention was measured by means of coding glances on and off the forward roadway.

Comparison of concurrent cognitive load measures during n-back tasks.

The cognitive load experienced by humans is an important factor affecting their performance. Cognitive overload or underload may result in suboptimal human performance and may compromise safety in emerging human-in-the-loop systems. In driving, cognitive overload, due to various secondary tasks, such as texting, results in driver distraction.

Adopting Stimulus Detection Tasks for Cognitive Workload Assessment: Some Considerations.

Objective: This article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator's workload.

Background: Stimulus detection tasks are a relative simple and inexpensive means of measuring the operator's state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic.

Preface to the Special Issue on Assessment and Effectiveness of Driver Monitoring Systems.

With vehicle automation becoming more commonplace, the role of the human driver is shifting from that of system operator to that of system supervisor. With this shift comes the risk of drivers becoming more disengaged from the task of supervising the system functioning, thus increasing the need for technology to keep drivers alert. This special issue includes the most up-to-date research on how drivers use vehicle automation, and the safety risks it may pose.

Vigilance Decrement During On-Road Partially Automated Driving Across Four Systems.

Objective: This study uses a detection task to measure changes in driver vigilance when operating four different partially automated systems.

Background: Research show temporal declines in detection task performance during manual and fully automated driving, but the accuracy of using this approach for measuring changes in driver vigilance during on-road partially automated driving is yet unproven.

Method: Participants drove four different vehicles (Tesla Model 3, Cadillac CT6, Volvo XC90, and Nissan Rogue) equipped with level-2 systems in manual and partially automated modes.

On the Effect of COVID-19 on Drivers' Behavior: A Survey Study.

COVID-19 had a disruptive effect on the global community. This study looks at the effects that the stringent lockdown measures enacted in March 2020 had on motorists' driving patterns. In particular, given the greater portability of remote working associated with the drastic decline in personal mobility, it is hypothesized that these may have served as accelerators for distracted and aggressive driving.

On the potential of pupil size as a metric of physical fatigue during a repeated handle push/pull task.

Force output and muscle activity represent the gold standards for measuring physical fatigue. This study explores using ocular metrics for tracking changes in physical fatigue during the completion of a repeated handle push/pull task. Participants completed this task over three trials, and pupil size was recorded by means of a head-mounted eye-tracker.

Distracted worker: Using pupil size and blink rate to detect cognitive load during manufacturing tasks.

This study sets out to extend the use of blink rate and pupil size to the assessment of cognitive load of completing common automotive manufacturing tasks. Nonoptimal cognitive load is detrimental to safety. Existing occupational ergonomics approaches come short of measuring dynamic changes in cognitive load during complex assembling tasks.

On the Cost of Detection Response Task Performance on Cognitive Load.

Objective: This study investigates the cost of detection response task performance on cognitive load.

Background: Measuring system operator's cognitive load is a foremost challenge in human factors and ergonomics. The detection response task is a standardized measure of cognitive load.

Overloaded and at Work: Investigating the Effect of Cognitive Workload on Assembly Task Performance.

Objective: This study investigates the effect of cognitive overload on assembly task performance and muscle activity.

Background: Understanding an operator's cognitive workload is an important component in assessing human-machine interaction. However, little evidence is available on the effect that cognitive overload has on task performance and muscle activity when completing manufacturing tasks.

Precision teaching to improve drivers' lane maintenance.

Introduction: This study investigates the effect of precision teaching signals on lane maintenance.

Methods: In experiment 1, the control group drove a simulator with no signals. In experiment 2, drivers were presented with auditory signals depending on their position within or outside the lane.