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

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

de Winter, J.C.F. (TU Delft Human-Robot Interaction; TU Delft Biomechatronics & Human-Machine Control)
Eisma, Y.B. (TU Delft Human-Robot Interaction; TU Delft Control & Simulation)
Cabrall, C.D.D. (TU Delft Intelligent Vehicles; TU Delft Biomechatronics & Human-Machine Control)
Hancock, P. A. (University of Central Florida)
Stanton, N. A. (University of Southampton)

2019

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.

Automatism
Eye movements
Operator state
Situated cognition

http://resolver.tudelft.nl/uuid:898d80b0-f052-41f2-a24a-3a8c083fa6ae

https://doi.org/10.1007/s10111-018-0527-6

1435-5558

Cognition, Technology and Work, 21 (1), 99-111

Institutional Repository

journal article

© 2019 J.C.F. de Winter, Y.B. Eisma, C.D.D. Cabrall, P. A. Hancock, N. A. Stanton