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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Nanyang Technological University
2023
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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 |
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Engineering::Aeronautical engineering Quek, Lionel Sze Yih Visual memory assessment methods for traffic control tasks |
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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. |
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Lye Sun Woh |
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Lye Sun Woh Quek, Lionel Sze Yih |
format |
Final Year Project |
author |
Quek, Lionel Sze Yih |
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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 |
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Visual memory assessment methods for traffic control tasks |
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Visual memory assessment methods for traffic control tasks |
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visual memory assessment methods for traffic control tasks |
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Nanyang Technological University |
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2023 |
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https://hdl.handle.net/10356/167583 |
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