Predicting Inattentional Blindness with Pupillary Response in a Simulated Flight Task
type: CreativeWork
description: Inattentional blindness (IB) is the failure of observers to notice the presence of a clearly viewable but unexpected visual event when attentional resources are diverted elsewhere. Knowing when an operator is unable to respond or detect an unexpected event may help improve safety during task performance. Unfortunately, it is difficult to predict when such failures might occur. The current study was a secondary data analysis of data collected in the Human and Autonomous Vehicle Systems Laboratory at NASA Langley Research Center. Specifically, 60 subjects (29 male, with normal or corrected-to-normal vision, mean age of 34.5 years (SD = 13.3) were randomly assigned to one of three automation conditions (full automation, partial automation, and full manual) and took part in a simulated flight landing task. The dependent variable was the detection/non-detection of an IB occurrence (a truck on the landing runway). Scores on the NASA-TLX workload rating scale varied significantly by automation condition. The full automation condition reported the lowest subjective task load followed by partial automation and then manual condition. IB detection varied significantly across automation condition. The moderate workload condition of partial automation exhibited the lowest likelihood of IB occurrence. The low workload full automation condition did not differ significantly from the manual condition. Subjects who reported higher task demand had increased pupil dilation and subjects with larger pupil dilation were more likely to detect the runway incursion. These results show eye tracking may be used to identify periods of reduced unexpected visual stimulus detection for possible real-time IB mitigation.
abstract: Inattentional blindness (IB) is the failure of observers to notice the presence of a clearly viewable but unexpected visual event when attentional resources are diverted elsewhere. Knowing when an operator is unable to respond or detect an unexpected event may help improve safety during task performance. Unfortunately, it is difficult to predict when such failures might occur. The current study was a secondary data analysis of data collected in the Human and Autonomous Vehicle Systems Laboratory at NASA Langley Research Center. Specifically, 60 subjects (29 male, with normal or corrected-to-normal vision, mean age of 34.5 years (SD = 13.3) were randomly assigned to one of three automation conditions (full automation, partial automation, and full manual) and took part in a simulated flight landing task. The dependent variable was the detection/non-detection of an IB occurrence (a truck on the landing runway). Scores on the NASA-TLX workload rating scale varied significantly by automation condition. The full automation condition reported the lowest subjective task load followed by partial automation and then manual condition. IB detection varied significantly across automation condition. The moderate workload condition of partial automation exhibited the lowest likelihood of IB occurrence. The low workload full automation condition did not differ significantly from the manual condition. Subjects who reported higher task demand had increased pupil dilation and subjects with larger pupil dilation were more likely to detect the runway incursion. These results show eye tracking may be used to identify periods of reduced unexpected visual stimulus detection for possible real-time IB mitigation.
author: Kennedy, Kellie D.
keywords: Aviation, Human Factors, Psychophysiology, Biological Psychology, Cognitive Psychology, Health Psychology, Human Factors Psychology
date published: 2021-07-01T07:00:00Z
date modified: 2026-07-24T03:35:38Z
provider: Old Dominion University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Old Dominion University