Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151964
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dc.contributor.authorZakaria, Zainuddinen_US
dc.contributor.authorLye, Sun Wohen_US
dc.date.accessioned2021-09-28T05:18:31Z-
dc.date.available2021-09-28T05:18:31Z-
dc.date.issued2021-
dc.identifier.citationZakaria, Z. & Lye, S. W. (2021). Unearthing air traffic control officer strategies from simulated air traffic data. 5th International Conference on Human Interaction and Emerging Technologies (IHIET 2021), 364-371. https://dx.doi.org/10.1007/978-3-030-85540-6_46en_US
dc.identifier.isbn978-3-030-85539-0-
dc.identifier.isbn978-3-030-85540-6-
dc.identifier.urihttps://hdl.handle.net/10356/151964-
dc.description.abstractWith the growth in air traffic volume, automation tools are being developed to increase the capabilities of Air Traffic Control Officers (ATCOs). In this paper, a novel approach to unearth Air Traffic Control (ATC) strategies from raw simulator data is described by utilizing executed radar commands obtained via mouse click data. Five sets of air traffic simulation exercise data were used to identify potential conflicts and unearth likely strategies undertaken using a proposed strategy identification model. The preliminary results demonstrate the success of the model in its ability to identify four distinct strategies adopted by the controllers to safely navigate air traffic conflicts that occurred during the simulation and the conflict type in which they occurred. Strategies identified were also verified by an expert panel to be effective in solving the targeted conflict type. The proposed model can be used to objectively identify ATC strategies for use in automation development.en_US
dc.description.sponsorshipCivil Aviation Authority of Singapore (CAAS)en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.language.isoenen_US
dc.rights© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG. All rights reserved. This paper was published by Springer Nature in Proceedings of 5th International Virtual Conference on Human Interaction and Emerging Technologies (IHIET 2021) and is made available with permission of The Author(s).en_US
dc.subjectEngineering::Aeronautical engineeringen_US
dc.titleUnearthing air traffic control officer strategies from simulated air traffic dataen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.conference5th International Conference on Human Interaction and Emerging Technologies (IHIET 2021)en_US
dc.contributor.researchAir Traffic Management Research Instituteen_US
dc.identifier.doi10.1007/978-3-030-85540-6_46-
dc.description.versionAccepted versionen_US
dc.identifier.spage364en_US
dc.identifier.epage371en_US
dc.subject.keywordsAir Traffic Controlen_US
dc.subject.keywordsHuman-systems Integrationen_US
dc.citation.conferencelocationVirtual Conferenceen_US
dc.description.acknowledgementThis project is supported by the Civil Aviation Authority of Singapore and Nanyang Technological University, Singapore under their collaboration in the Air Traffic Management Research Institute.en_US
item.grantfulltextembargo_20220917-
item.fulltextWith Fulltext-
Appears in Collections:ATMRI Conference Papers
MAE Conference Papers
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