Visual memory assessment methods for traffic control tasks

Aviation is a constantly growing industry, with improvements in aircraft technology and the steady increasing demand for commercial flights post-COVID19 pandemic. To cope with the increase in traffic, air traffic controllers must be able to maintain situation awareness in the form of working memory...

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Main Author: Quek, Lionel Sze Yih
Other Authors: Lye Sun Woh
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167583
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1675832023-06-03T16:50:28Z Visual memory assessment methods for traffic control tasks Quek, Lionel Sze Yih Lye Sun Woh School of Mechanical and Aerospace Engineering MSWLYE@ntu.edu.sg Engineering::Aeronautical engineering Aviation is a constantly growing industry, with improvements in aircraft technology and the steady increasing demand for commercial flights post-COVID19 pandemic. To cope with the increase in traffic, air traffic controllers must be able to maintain situation awareness in the form of working memory of the aircraft they are controlling within a sector, hence, quantifying traffic situations would better help discover potential performance limits. In this report, a study was conducted to develop a framework to quantify aircraft information complexity. Experiments replicating auditory, associative, and sequential scenarios were conducted to study their inherent complexities that can add or subtract to a total scenario complexity value. Additional behavioural observations were also made during experiments to learn information complexity effects on recall performance. The outcome of this study can be used as a steppingstone to further define traffic scenario complexities and discover performance limits of traffic controllers. This can help develop future traffic control standard operating procedures and system optimisations. Bachelor of Engineering (Aerospace Engineering) 2023-05-30T06:55:26Z 2023-05-30T06:55:26Z 2023 Final Year Project (FYP) Quek, L. S. Y. (2023). Visual memory assessment methods for traffic control tasks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167583 https://hdl.handle.net/10356/167583 en B156 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
Quek, Lionel Sze Yih
Visual memory assessment methods for traffic control tasks
description Aviation is a constantly growing industry, with improvements in aircraft technology and the steady increasing demand for commercial flights post-COVID19 pandemic. To cope with the increase in traffic, air traffic controllers must be able to maintain situation awareness in the form of working memory of the aircraft they are controlling within a sector, hence, quantifying traffic situations would better help discover potential performance limits. In this report, a study was conducted to develop a framework to quantify aircraft information complexity. Experiments replicating auditory, associative, and sequential scenarios were conducted to study their inherent complexities that can add or subtract to a total scenario complexity value. Additional behavioural observations were also made during experiments to learn information complexity effects on recall performance. The outcome of this study can be used as a steppingstone to further define traffic scenario complexities and discover performance limits of traffic controllers. This can help develop future traffic control standard operating procedures and system optimisations.
author2 Lye Sun Woh
author_facet Lye Sun Woh
Quek, Lionel Sze Yih
format Final Year Project
author Quek, Lionel Sze Yih
author_sort Quek, Lionel Sze Yih
title Visual memory assessment methods for traffic control tasks
title_short Visual memory assessment methods for traffic control tasks
title_full Visual memory assessment methods for traffic control tasks
title_fullStr Visual memory assessment methods for traffic control tasks
title_full_unstemmed Visual memory assessment methods for traffic control tasks
title_sort visual memory assessment methods for traffic control tasks
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167583
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