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Development and Proof of Concept of a Predictive Model of Flight Deck Cognitive Workload

  • Don Harris
  • , Steve Scott

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Workload can be regarded as the “cost” (in information processing terms) of performing a given flight task. Predictive models of workload are valuable at the early stages of system design to identify potentially excessive demands on the human operator before major system development commences. This paper describes the early development of a task-based predictive workload method. It utilizes a scenario-based timeline analysis supplemented by characterizations of the cognitive nature of the pilot’s tasks using Wickens’ multiple resource theory, followed by the identification of likely task conflicts and estimates of the influence of the task environment. Workload predictions were made for a manual approach, landing and roll-out scenario in a modern airliner. Predictions were compared against corresponding Bedford scale workload estimates. Results show that the predictive workload technique produced comparable estimates of cognitive workload measured using the Bedford scale.

    Original languageEnglish
    Pages (from-to)38-48
    Number of pages11
    JournalAviation Psychology and Applied Human Factors
    Volume14
    Issue number1
    DOIs
    Publication statusPublished - 26 Jul 2024

    Funder

    This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No. 945583. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.

    Funding

    This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No. 945583. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.

    FundersFunder number
    Clean Aviation945583
    Horizon Europe

      Keywords

      • workload
      • workload modeling
      • workload prediction
      • task analysis

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