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Combining time and intensity effects in assessing operator information-processing load

K C Hendy1, J Liao, P Milgram

  • 1Defence and Civil Institute of Environmental Medicine, North York, Ontario, Canada.

Human Factors
|March 1, 1997
PubMed
Summary
This summary is machine-generated.

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This study introduces a new model for human information processing, linking time pressure to operator workload and performance. The findings suggest that the ratio of processing time to decision time is key for predicting operator load.

Area of Science:

  • Human-Computer Interaction
  • Cognitive Psychology
  • Systems Engineering

Background:

  • Predicting operator workload and performance requires a quantitative human information processor model.
  • Existing workload models lack theoretical grounding and quantitative representation of operator load.
  • Both time- and intensity-based factors may influence operator workload and performance.

Purpose of the Study:

  • To investigate the relationship between time-based and intensity-based factors in operator load.
  • To develop a quantitative model for predicting operator workload and performance.
  • To test the proposed model in a simulated air traffic control environment.

Main Methods:

  • Developed a model where human information processing load is a ratio of necessary processing time to allowable decision time.

Related Experiment Videos

  • Investigated this ratio, identified as time pressure, in a simulated air traffic control (ATC) setting.
  • Tested the model against simulation data to assess its predictive power.

    • Main Results:

    • The proposed model posits that time pressure directly influences subjective workload estimates.
    • Operator performance is also shown to be determined by this time pressure ratio.
    • The model was validated using data from the air traffic control simulation.

    Conclusions:

    • A quantitative model based on the time pressure ratio effectively predicts operator workload.
    • Both subjective workload and objective performance are linked to the information processing load.
    • The findings support a unified approach to understanding operator load in complex environments.