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Exploring the Potential for Metrics of Cognitive Workload to Measure Situational Awareness

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  • معلومة اضافية
    • بيانات النشر:
      University of Windsor
    • الموضوع:
      2024
    • Collection:
      University of Windsor, Ontario: Scholarship at UWindsor
    • نبذة مختصرة :
      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.
    • File Description:
      application/pdf
    • Relation:
      https://scholar.uwindsor.ca/etd/9477; https://scholar.uwindsor.ca/context/etd/article/10483/viewcontent/1069776.pdf
    • الدخول الالكتروني :
      https://scholar.uwindsor.ca/etd/9477
      https://scholar.uwindsor.ca/context/etd/article/10483/viewcontent/1069776.pdf
    • Rights:
      http://creativecommons.org/licenses/by/4.0/
    • الرقم المعرف:
      edsbas.33A25EDA