Situation awareness based on eye movements in relation to the task environment

Journal article (2019)

Authors

J.C.F. de Winter Human-Robot Interaction - Mechanical, Maritime and Materials Engineering , Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
Y.B. Eisma Human-Robot Interaction - Mechanical, Maritime and Materials Engineering ,
C.D.D. Cabrall Intelligent Vehicles - Mechanical, Maritime and Materials Engineering , Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
P. A. Hancock University of Central Florida
Neville A. Stanton University of Southampton
Research Group
Biomechatronics & Human-Machine Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2019 J.C.F. de Winter, Y.B. Eisma, C.D.D. Cabrall, P. A. Hancock, N. A. Stanton
DOI: https://doi.org/10.1007/s10111-018-0527-6
More Info
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Published Date

2019

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Biomechanical Engineering

Research Group

Biomechatronics & Human-Machine Control

Abstract

The topic of situation awareness has received continuing interest over the last decades. Freeze-probe methods, such as the Situation Awareness Global Assessment Technique (SAGAT), are commonly employed for measuring situation awareness. The aim of this paper was to review validity issues of the SAGAT and examine whether eye movements are a promising alternative for measuring situation awareness. First, we outlined six problems of freeze-probe methods, such as the fact that freeze-probe methods rely on what the operator has been able to remember and then explicitly recall. We propose an operationalization of situation awareness based on the eye movements of the person in relation to their task environment to circumvent shortfalls of memory mediation and task interruption. Next, we analyzed experimental data in which participants (N = 86) were tasked to observe a display of six dials for about 10 min, and press the space bar if a dial pointer crossed a threshold value. Every 90 s, the screen was blanked and participants had to report the state of the dials on a paper sheet. We assessed correlations of participants’ task performance (% of threshold crossing detected) with visual sampling scores (% of dials glanced at during threshold crossings) and freeze-probe scores. Results showed that the visual-sampling score correlated with task performance at the threshold-crossing level (r = 0.31) and at the individual level (r = 0.78). Freeze-probe scores were low and showed weak associations with task performance. We conclude that the outlined limitations of the SAGAT impede measurement of situation awareness, which can be computed more effectively from eye movement measurements in relation to the state of the task environment. The present findings have practical value, as advances in eye-tracking cameras and ubiquitous computing lessen the need for interruptive tests such as SAGAT. Eye-based situation awareness is a predictor of performance, with the advantage that it is applicable through real-time feedback technologies.