Multivariate Analysis of Gaze Behaviour and Task Performance within Interface Design Evaluation

James Blundell, Charlotte Collins, Rod Sears, Anastasios Plioutsias, John Huddlestone, Don Harris, James Harrison, Anthony Kershaw, Paul Harrison, Phil Lamb

Research output: Contribution to journalArticlepeer-review

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Abstract

Eye tracking technologies have frequently been used in sport research to understand the interrelations between gaze behavior and performance, using a paradigm known as vision-for-action. This methodology has not been robustly applied within the field of interface design. The present work demonstrates the benefit of employing a vision-for-action paradigm for interface evaluation. This is demonstrated through the evaluation of a novel task-specific symbology set presented on a head-up-display (HUD), developed to support pilots conduct ground operations in low-visibility conditions. HUD gaze behavior was correlated with task performance to determine whether certain combinations of gaze behavior could produce effective predictive performance models. A human-in-the-loop experiment was conducted with 11 professional pilots who were required to taxi in a fixed-base flight simulator using the HUD symbology, whilst gaze data towards the different HUD symbology elements was collected. Performance was measured as centerline deviation error and taxiing speed. Results revealed that appropriately timed gaze behaviors towards task-specific elements of the HUD were associated with superior performance. During turns, attention towards an undercarriage lateral position indicator was associated with reduced centerline deviation (p
Original languageEnglish
Pages (from-to)875-884
Number of pages10
JournalIEEE Transactions on Human-Machine Systems
Volume53
Issue number5
Early online date31 Aug 2023
DOIs
Publication statusPublished - Oct 2023

Bibliographical note

This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.

Funder

Aerospace Technology Institute (ATI) Programme (Grant Number: 113108)
Government and Industry Investment to Maintain and Grow
U.K.’s competitive position in civil aerospace design and manufacture
ATI
Department for Business
Energy & Industrial Strategy and Innovate U.K.

Keywords

  • eye tracking
  • human performance
  • Head-up display
  • multivariate analysis
  • interface design

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