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Title: Unearthing ATCO decision instructional pattern from simulator data
Authors: Zakaria, Zainuddin
Lye, Sun Woh
Endy, Susanto
Keywords: Engineering
Issue Date: 2023
Source: 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).
Conference: 6th International Conference on Computer and Electrical Engineering (ICCEE 2023)
Abstract: 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.
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Air Traffic Management Research Institute 
Rights: © 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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers

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