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Characterization of Visual Scanning Patterns in Air Traffic Control.

Sarah N McClung1, Ziho Kang2

  • 1School of Electrical and Computer Engineering, University of Oklahoma, 110 W. Boyd Street, Devon Energy Hall 150, Norman, OK 73019-1102, USA.

Computational Intelligence and Neuroscience
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Summary

Analyzing air traffic controllers' (ATCs) visual scanning strategies is complex. New methods simplify scanpath analysis, linking eye movements to linguistic reports and revealing how aircraft congestion impacts controller attention.

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Area of Science:

  • Human Factors
  • Cognitive Psychology
  • Aerospace Engineering

Background:

  • Characterizing air traffic controllers' (ATCs) visual scanning strategies is challenging due to dynamic environments and complex scanpaths.
  • Existing methods lack standardized terminology and procedures for analyzing eye-tracking data into simplified visual scanning strategies.
  • Automating the analysis of ATC visual behavior is crucial for improving safety and efficiency.

Purpose of the Study:

  • To develop and validate new concepts for simplifying complex visual scanpaths.
  • To create procedures for mapping visual scanpaths with linguistic inputs from ATCs.
  • To investigate the influence of aircraft congestion on ATC visual scanning behavior and oculomotor trends.

Main Methods:

  • Defined and developed novel concepts to systematically filter complex visual scanpaths.
  • Created procedures to map visual scanpaths with linguistic inputs, reducing interrater bias.
  • Applied methods to expert ATCs' scanpaths across varying aircraft congestion scenarios and analyzed oculomotor trends.

Main Results:

  • Scanpaths filtered at higher intensity showed more consistent mapping with ATCs' linguistic inputs.
  • Visual scanpath pattern occurrences varied significantly between different aircraft congestion scenarios.
  • Increased aircraft congestion correlated with longer scan times and a higher number of aircraft pairwise comparisons.

Conclusions:

  • The developed methods provide a foundation for systematically characterizing complex visual scanpaths in dynamic tasks.
  • Automating the analysis of visual scanning strategies can enhance understanding of ATC performance.
  • Findings highlight the impact of aircraft congestion on ATC visual attention and cognitive load.