Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study
In many domains, including air traffic control, observers have to detect conflicts between moving objects. However, it is unclear what the effect of conflict angle is on observers’ conflict detection performance. In addition, it has been speculated that observers use specific viewing techniques whil...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-07-01
|
Series: | Vision |
Subjects: | |
Online Access: | https://www.mdpi.com/2411-5150/4/3/34 |
_version_ | 1827712579276898304 |
---|---|
author | Yke Bauke Eisma Anouk E. Looijestijn Joost C. F. de Winter |
author_facet | Yke Bauke Eisma Anouk E. Looijestijn Joost C. F. de Winter |
author_sort | Yke Bauke Eisma |
collection | DOAJ |
description | In many domains, including air traffic control, observers have to detect conflicts between moving objects. However, it is unclear what the effect of conflict angle is on observers’ conflict detection performance. In addition, it has been speculated that observers use specific viewing techniques while performing a conflict detection task, but evidence for this is lacking. In this study, participants (<i>N</i> = 35) observed two converging objects while their eyes were recorded. They were tasked to continuously indicate whether a conflict between the two objects was present. Independent variables were conflict angle (30, 100, 150 deg), update rate (discrete, continuous), and conflict occurrence. Results showed that 30 deg conflict angles yielded the best performance, and 100 deg conflict angles the worst. For 30 deg conflict angles, participants applied smooth pursuit while attending to the objects. In comparison, for 100 and especially 150 deg conflict angles, participants showed a high fixation rate and glances towards the conflict point. Finally, the continuous update rate was found to yield shorter fixation durations and better performance than the discrete update rate. In conclusion, shallow conflict angles yield the best performance, an effect that can be explained using basic perceptual heuristics, such as the ‘closer is first’ strategy. Displays should provide continuous rather than discrete update rates. |
first_indexed | 2024-03-10T18:17:45Z |
format | Article |
id | doaj.art-3df9f193bea74c25bb7ef7fa792cb656 |
institution | Directory Open Access Journal |
issn | 2411-5150 |
language | English |
last_indexed | 2024-03-10T18:17:45Z |
publishDate | 2020-07-01 |
publisher | MDPI AG |
record_format | Article |
series | Vision |
spelling | doaj.art-3df9f193bea74c25bb7ef7fa792cb6562023-11-20T07:32:09ZengMDPI AGVision2411-51502020-07-01433410.3390/vision4030034Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking StudyYke Bauke Eisma0Anouk E. Looijestijn1Joost C. F. de Winter2Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, 2628 CD Delft, The NetherlandsDepartment of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, 2628 CD Delft, The NetherlandsDepartment of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, 2628 CD Delft, The NetherlandsIn many domains, including air traffic control, observers have to detect conflicts between moving objects. However, it is unclear what the effect of conflict angle is on observers’ conflict detection performance. In addition, it has been speculated that observers use specific viewing techniques while performing a conflict detection task, but evidence for this is lacking. In this study, participants (<i>N</i> = 35) observed two converging objects while their eyes were recorded. They were tasked to continuously indicate whether a conflict between the two objects was present. Independent variables were conflict angle (30, 100, 150 deg), update rate (discrete, continuous), and conflict occurrence. Results showed that 30 deg conflict angles yielded the best performance, and 100 deg conflict angles the worst. For 30 deg conflict angles, participants applied smooth pursuit while attending to the objects. In comparison, for 100 and especially 150 deg conflict angles, participants showed a high fixation rate and glances towards the conflict point. Finally, the continuous update rate was found to yield shorter fixation durations and better performance than the discrete update rate. In conclusion, shallow conflict angles yield the best performance, an effect that can be explained using basic perceptual heuristics, such as the ‘closer is first’ strategy. Displays should provide continuous rather than discrete update rates.https://www.mdpi.com/2411-5150/4/3/34conflict detectioneye-trackingsmooth pursuit |
spellingShingle | Yke Bauke Eisma Anouk E. Looijestijn Joost C. F. de Winter Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study Vision conflict detection eye-tracking smooth pursuit |
title | Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study |
title_full | Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study |
title_fullStr | Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study |
title_full_unstemmed | Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study |
title_short | Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study |
title_sort | attention distribution while detecting conflicts between converging objects an eye tracking study |
topic | conflict detection eye-tracking smooth pursuit |
url | https://www.mdpi.com/2411-5150/4/3/34 |
work_keys_str_mv | AT ykebaukeeisma attentiondistributionwhiledetectingconflictsbetweenconvergingobjectsaneyetrackingstudy AT anoukelooijestijn attentiondistributionwhiledetectingconflictsbetweenconvergingobjectsaneyetrackingstudy AT joostcfdewinter attentiondistributionwhiledetectingconflictsbetweenconvergingobjectsaneyetrackingstudy |