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Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
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A Multidimensional Method for Pilot Workload Assessment and Diagnosis.

Zhen Wang, Yanyu Lu, Shan Fu

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    |November 27, 2020
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    Summary
    This summary is machine-generated.

    This study developed a novel pilot workload assessment method using physiological and behavioral data. The method effectively distinguishes workload differences and provides diagnostic insights for flight safety and cockpit design.

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    Area of Science:

    • Human Factors Engineering
    • Aerospace Psychology
    • Aviation Safety

    Background:

    • Pilot workload assessment is critical for flight safety, interface design, and airworthiness.
    • Developing reliable workload assessment methods presents a significant challenge in human factors research.

    Purpose of the Study:

    • To propose and validate a multi-dimensional pilot workload assessment method.
    • To evaluate the method's effectiveness in distinguishing workload variations across different flight phases.

    Main Methods:

    • Assessed pilot workload across four dimensions: cognitive activity, control activity, stress, and flight performance.
    • Utilized a combination of physiological, behavioral, and flight parameters.
    • Conducted a simulated flight experiment with three distinct flight phases.

    Main Results:

    • The proposed method effectively differentiated workload levels based on task difficulty, aligning with NASA-TLX results.
    • Detailed workload variations were identified across flight phases, with nonprecision approaches showing higher control activity and stress.
    • Autopilot cruise phases exhibited the lowest control activity and highest flight performance.

    Conclusions:

    • The developed method provides an effective and diagnostic tool for pilot workload assessment.
    • This approach can serve as an auxiliary tool for pilot-cockpit interaction development and evaluation.