Self-organising maps for comparing flying performance using different inceptors

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dc.contributor.authorNichanian, Arthur
dc.contributor.authorLi, Wen-Chin
dc.contributor.authorKorek, Wojciech Tomasz
dc.contributor.authorWang, Yifan
dc.contributor.authorChan, Wesley Tsz-Kin
dc.date.accessioned2024-07-29T15:45:42Z
dc.date.available2024-07-29T15:45:42Z
dc.date.freetoread2024-07-29
dc.date.issued2024-06-01
dc.description.abstractThis paper addresses a new data analysis method which is suitable to cluster flight data and complement current exceedance-based flight data monitoring programmes within an airline. The data used for this study consists of 296 simulated approaches from 4.5 NM to 1 NM to the runway threshold, flown by 74 participants (both pilots and non-pilots) with either a conventional sidestick or a gamepad in the future flight simulator at Cranfield University. It was clustered and analysed with the use of Kohonen’s Self-Organising Maps (SOM) algorithm. The results demonstrate that SOM can be a meaningful indicator for safety analysts to accurately cluster both optimal and less-optimal flying performance. This methodology can therefore complement current deviation-based flight data analyses by highlighting day-to-day as well as exceptionally good performance, bridging the cap of current analyses with safety-II principles.
dc.description.conferencename21st International Conference, EPCE 2024, Held as Part of the 26th HCI International Conference, HCII 2024
dc.format.extent109-122
dc.identifier.citationNichanian A, Li W-C, Korek WT (2024) Self-organising maps for comparing flying performance using different inceptors. In: 21st International Conference, EPCE 2024, Held as Part of the 26th HCI International Conference, HCII 2024, 29 June - 4 July 2024, Washington DC, USA. Proceedings, Part II, Lecture Notes in Computer Science, Volume 14693, pp. 109-122
dc.identifier.eisbn978-3-031-60731-8
dc.identifier.eissn1611-3349
dc.identifier.isbn978-3-031-60730-1
dc.identifier.issn0302-9743
dc.identifier.urihttps://doi.org/10.1007/978-3-031-60731-8_8
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22681
dc.language.isoen
dc.publisherSpringer
dc.publisher.urihttps://link.springer.com/chapter/10.1007/978-3-031-60731-8_8
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectdata analysis
dc.subjecthuman-machine interactions
dc.titleSelf-organising maps for comparing flying performance using different inceptors
dc.typeConference paper
dcterms.coverageWashington DC, USA
dcterms.temporal.endDate04-Jul-2024
dcterms.temporal.startDate29-Jun-2024

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