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Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination.

Yeti Li1, Catherine M Burns1

  • 1University of Waterloo.

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|October 30, 2018
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Summary

We propose a degree of automation (DOA) layering approach to enhance human-automation coordination. This method models function allocation for better interface design in complex automated systems.

Keywords:
abstraction hierarchyautomated financial tradingcognitive work analysisdecision ladderdegree of automationhuman-automation interactionstages and levels of automation

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Area of Science:

  • Human-Computer Interaction
  • Cognitive Systems Engineering
  • Automation and Control

Background:

  • Cognitive Work Analysis (CWA) is valuable for complex system displays but underexplored for human-automation coordination.
  • Existing CWA methods may not adequately represent modern automated systems with varying degrees of automation.

Purpose of the Study:

  • To propose and demonstrate a Degree of Automation (DOA) layering approach for CWA.
  • To support interface design for human-automation coordination in complex domains.
  • To enhance the representation of automation in CWA.

Main Methods:

  • Developed a DOA layering approach by adding a layer to the abstraction hierarchy and decision ladder.
  • Mapped functions allocated to human operators and automation within the model.
  • Incorporated four stages of automation onto the decision ladder for task-level guidance.
  • Modeled an automated financial trading domain to demonstrate the approach.

Main Results:

  • The DOA-layered decision ladder effectively represents automation across different stages and levels.
  • The approach is suitable for modern automated systems with diverse DOAs.
  • Comparison with existing CWA literature highlighted the novelty and utility of the DOA layering.

Conclusions:

  • The DOA layering approach offers significant implications for designing automation displays and defining automation levels.
  • This method provides a useful framework for modeling adaptive automation.
  • It enhances the representation of human-automation coordination within Cognitive Work Analysis.