Date of Award

5-16-2024

Publication Type

Thesis

Degree Name

M.H.K.

Department

Kinesiology

Keywords

Cognitive Workload;Haemoglobin;NIRS;SAGAT;Situation Awareness;Virtual Reality

Supervisor

FRANCESCO BIONDI

Supervisor

ANTHONY BAIN

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This study examines the relationship between workload (CW) and situational awareness (SA) in autonomous vehicles. We investigated (1) whether CW metrics can predict SA, and (2) the long-term effects of automated driving on cognitive demands. Participants experienced a simulated autonomous driving scenario. Established CW metrics (oxygenated haemoglobin, pupil diameter, response times, eye openness) exhibited a significant increase throughout the task, despite its inherent boredom. Notably, oxygenated haemoglobin (O2Hb) in the prefrontal cortex, a key indicator of workload, displayed the strongest rise. This suggests participants exerted more mental effort, possibly to combat perceived dullness. However, SA scores showed a concerning decline, indicating reduced awareness. Surprisingly, heightened CW did not translate to improved SA, suggesting inefficient allocation of cognitive resources. This aligns with the Yerkes-Dodson model, where performance worsens with excessive workload. This unexpected surge suggests participants exerted greater mental effort despite the inherent boredom of the task, potentially due to the brain actively seeking stimulation to combat perceived dullness. Boredom may be a key factor driving attention away from primary tasks. This constant struggle to stay focused in the face of boredom can lead to stress and fatigue. This study contributes to the CW-SA interplay and enhances our understanding of human-machine interaction in autonomous vehicles, leading to safer designs and potentially reliable objective measures of SA.

Download

Share

COinS