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Using Eye-Tracking Analysis to Detect Pilot Focus in Drone Interfaces During Signal Loss

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Augmented Cognition (HCII 2025)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 15778))

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Abstract

Signal interruptions remain a critical challenge in drone operations, as losing connection to the operator can result in sudden, high-stress scenarios with potential safety implications. This paper presents an investigation using mobile eye-tracking technology to examine how both novice and experienced drone pilots allocate their visual attention when confronted with total signal loss. Fifty-six participants (11 experienced, 45 novice) completed a standardized flight task during which the drone’s connection was deliberately disrupted. Quantitative data, including heatmaps and eye-tracking metrics, provided evidence of pronounced differences between the two groups. Novices exhibited dispersed scanning patterns and slower recognition of critical alerts, suggesting higher cognitive load. In contrast, experienced pilots rapidly identified key alerts, indicated by shorter time to first fixation and more focused fixations on essential interface icons such as the signal-strength indicator. Qualitative feedback from post-flight interviews further supported these findings: novices reported confusion and a preference for larger, centrally placed notifications, whereas experienced pilots relied on ingrained scanning routines. Taken together, these results underline the importance of intuitive, attention-guiding user interfaces and targeted training interventions to enhance situational awareness and mitigate risks during unexpected signal-loss events.

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Acknowledgments

This publication was co-funded by the European Union under the Grant Agreement 101103592. Its contents are the sole responsibility of the EPIIC (Enhanced Pilot Interfaces & Interactions for fighter Cockpit) Consortium and do not necessarily reflect the views of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.

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Authors and Affiliations

  1. Computer Engineering and Informatics Department, Patras University, Patras, Greece

    Dimosthenis Minas, Angelos Fotopoulos, Michalis Xenos & Christos Zotos

Authors
  1. Dimosthenis Minas
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  2. Angelos Fotopoulos
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  3. Michalis Xenos
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  4. Christos Zotos
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Corresponding author

Correspondence to Dimosthenis Minas .

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  1. Soar Technology Inc., Orlando, FL, USA

    Dylan D. Schmorrow

  2. Katmai Government Services, Orlando, FL, USA

    Cali M. Fidopiastis

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Minas, D., Fotopoulos, A., Xenos, M., Zotos, C. (2025). Using Eye-Tracking Analysis to Detect Pilot Focus in Drone Interfaces During Signal Loss. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2025. Lecture Notes in Computer Science(), vol 15778. Springer, Cham. https://doi.org/10.1007/978-3-031-93724-8_4

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  • DOI: https://doi.org/10.1007/978-3-031-93724-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-93723-1

  • Online ISBN: 978-3-031-93724-8

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