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Virtual/augmented reality-based human-machine interface and interaction modes in airport control towers.

Sara Bagassi1, Marzia Corsi2, Francesca De Crescenzio2

  • 1Department of Industrial Engineering, University of Bologna, 47121, Forlì, Italy. sara.bagassi@unibo.it.

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Summary

This study introduces a virtual and augmented reality interface for air traffic control towers, enhancing operator situational awareness and performance. The system supports head-up operation, improving reaction times in critical scenarios.

Keywords:
Air traffic controlAirport control towerAugmented realityHuman machine interfaceMultimodal interactionSafety nets

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Area of Science:

  • Human-Computer Interaction
  • Aerospace Engineering
  • Virtual and Augmented Reality

Background:

  • Traditional airport control towers face challenges with operator situational awareness and performance.
  • The need for advanced human-machine interfaces (HMIs) is critical for air traffic control (ATC) operations, especially in low visibility.

Purpose of the Study:

  • To develop and validate an innovative HMI using virtual and augmented reality (VR/AR) for ATC operators.
  • To enhance human performance and situational awareness in airport control towers.

Main Methods:

  • Development of a VR/AR-based HMI with see-through head-mounted displays.
  • Implementation of features like adaptive HMI, multimodal interaction, and attention guidance.
  • Validation through human-in-the-loop real-time exercises on a dedicated simulation platform.

Main Results:

  • The developed VR/AR interface concept is operationally and technically feasible.
  • The system effectively supports air traffic controllers in maintaining a head-up position, even in low visibility.
  • Demonstrated reduction in reaction time during critical situations, positively impacting human performance.

Conclusions:

  • VR/AR technologies offer a viable solution for improving ATC operations.
  • The proposed interface enhances controller effectiveness and usability.
  • Further refinements are identified to optimize the HMI for future applications.