Unearthing ATCO decision instructional pattern from simulator data
Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resoluti...
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sg-ntu-dr.10356-1735042024-02-13T15:30:52Z Unearthing ATCO decision instructional pattern from simulator data Zakaria, Zainuddin Lye, Sun Woh Endy, Susanto School of Mechanical and Aerospace Engineering 6th International Conference on Computer and Electrical Engineering (ICCEE 2023) Air Traffic Management Research Institute Engineering Air Traffic Control Strategies Conflict Resolution Simulator Data Strategy Classification System Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers. Civil Aviation Authority of Singapore (CAAS) Submitted/Accepted version This project is supported by the Civil Aviation Authority of Singapore and Nanyang Technological University, Singapore, under their collaboration with the Air Traffic Management Research Institute and contribution from the Thales Group. 2024-02-09T02:04:48Z 2024-02-09T02:04:48Z 2023 Conference Paper Zakaria, Z., Lye, S. W. & Endy, S. (2023). Unearthing ATCO decision instructional pattern from simulator data. 6th International Conference on Computer and Electrical Engineering (ICCEE 2023). https://hdl.handle.net/10356/173504 https://iccee.org/iccee2023.html en © 2023 The Author(s). All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. application/pdf |
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Engineering Air Traffic Control Strategies Conflict Resolution Simulator Data Strategy Classification System |
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Engineering Air Traffic Control Strategies Conflict Resolution Simulator Data Strategy Classification System Zakaria, Zainuddin Lye, Sun Woh Endy, Susanto Unearthing ATCO decision instructional pattern from simulator data |
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Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Zakaria, Zainuddin Lye, Sun Woh Endy, Susanto |
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Conference or Workshop Item |
author |
Zakaria, Zainuddin Lye, Sun Woh Endy, Susanto |
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Zakaria, Zainuddin |
title |
Unearthing ATCO decision instructional pattern from simulator data |
title_short |
Unearthing ATCO decision instructional pattern from simulator data |
title_full |
Unearthing ATCO decision instructional pattern from simulator data |
title_fullStr |
Unearthing ATCO decision instructional pattern from simulator data |
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Unearthing ATCO decision instructional pattern from simulator data |
title_sort |
unearthing atco decision instructional pattern from simulator data |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/173504 https://iccee.org/iccee2023.html |
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