Effects of integrated takeover request warning with personal portable device on takeover time and post-takeover performance in level 3 driving automation.

Introduction: Level 3 driving automation defined by the Society of Automotive Engineers (SAE) requests human drivers to drive manually when the vehicle cannot perform the driving task. In this regard, researchers have studied the integrated takeover request (TOR) which provides visual and auditory TOR warning in both vehicle interface (e.g.

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.

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.

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.

Experimental data on open circuit voltage characterization for Li-ion batteries.

In this article, we present the datasets collected from nine different Li-ion batteries. These datasets contain voltage, current and time measurements during a full charge-discharge cycle of a battery at very low current (that is nearly at rate). Such low current rate data is suitable for open circuit voltage characterization.

Response time and eye tracking datasets for activities demanding varying cognitive load.

The dataset contains the following three measures that are widely used to determine cognitive load in humans: Detection Response Task - response time, pupil diameter, and eye gaze. These measures were recorded from 28 participants while they underwent tasks that are designed to permeate three different cognitive difficulty levels. The dataset will be useful to those researchers who seek to employ low cost, non-invasive sensors to detect cognitive load in humans and to develop algorithms for human-system automation.

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.