Identifying physiological thresholds in human performance for adaptive automation triggers

This research describes an approach to an objective assessment of conflict detection in an air traffic control setting by analysing differences in several aspects of the eye metrics such as fixation counts, fixation duration, and successive comparison in fixation targets. In an experiment, these are...

Full description

Saved in:
Bibliographic Details
Main Author: Lam, Xin He
Other Authors: Chen Chun-Hsien
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/150994
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-150994
record_format dspace
spelling sg-ntu-dr.10356-1509942021-06-15T06:00:45Z Identifying physiological thresholds in human performance for adaptive automation triggers Lam, Xin He Chen Chun-Hsien School of Mechanical and Aerospace Engineering MCHchen@ntu.edu.sg Engineering::Aeronautical engineering This research describes an approach to an objective assessment of conflict detection in an air traffic control setting by analysing differences in several aspects of the eye metrics such as fixation counts, fixation duration, and successive comparison in fixation targets. In an experiment, these areas were measured with an eye-tracking device. The successive comparison revealed a great difference between the two states of conflict detection while fixation count and duration did not show any significant differences. This assessment can be a trigger and be potentially integrated into an adaptive automation model to aid operators in the event they fail to perform. Bachelor of Engineering (Aerospace Engineering) 2021-06-15T06:00:45Z 2021-06-15T06:00:45Z 2021 Final Year Project (FYP) Lam, X. H. (2021). Identifying physiological thresholds in human performance for adaptive automation triggers. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150994 https://hdl.handle.net/10356/150994 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Aeronautical engineering
spellingShingle Engineering::Aeronautical engineering
Lam, Xin He
Identifying physiological thresholds in human performance for adaptive automation triggers
description This research describes an approach to an objective assessment of conflict detection in an air traffic control setting by analysing differences in several aspects of the eye metrics such as fixation counts, fixation duration, and successive comparison in fixation targets. In an experiment, these areas were measured with an eye-tracking device. The successive comparison revealed a great difference between the two states of conflict detection while fixation count and duration did not show any significant differences. This assessment can be a trigger and be potentially integrated into an adaptive automation model to aid operators in the event they fail to perform.
author2 Chen Chun-Hsien
author_facet Chen Chun-Hsien
Lam, Xin He
format Final Year Project
author Lam, Xin He
author_sort Lam, Xin He
title Identifying physiological thresholds in human performance for adaptive automation triggers
title_short Identifying physiological thresholds in human performance for adaptive automation triggers
title_full Identifying physiological thresholds in human performance for adaptive automation triggers
title_fullStr Identifying physiological thresholds in human performance for adaptive automation triggers
title_full_unstemmed Identifying physiological thresholds in human performance for adaptive automation triggers
title_sort identifying physiological thresholds in human performance for adaptive automation triggers
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/150994
_version_ 1703971165245014016