Augmented Reality in Extra-Vehicular Activities: Optimizing Alert Detection and Cognitive Workload
Year: 2024
Type: article
Abstract: This study investigates the impact of augmented reality (AR) system complexity (active vs. passive) and lighting conditions (normal, dark, glare) on task performance, cognitive workload, and alert detection during simulated extravehicular activities (EVAs). Fifty-eight undergraduate students participated, using AR systems to complete tasks. Key metrics included task completion rate, completion time, alert detection, and cognitive workload assessed by the NASA Task Load Index (NASA-TLX). Results showed no significant differences in task performance or cognitive workload across lighting conditions and AR types. Notably, less than 15% of participants noticed any alerts, suggesting AR alerts may lack sufficient salience. The study’s lack of significant findings is attributed to the small sample size and potential insensitivity of measures. Future research should involve larger samples and refined methodologies to better understand AR’s impact on astronaut performance and safety during EVAs.
Institutions: Rice University, Georgia Institute of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,200
OpenAlex ID: W4402380397