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Investigation of the Action Sequence of Pilots during Landing using Markov Models

Oberle, Marius ; König, Christina ; Bruder, Ralph
Hrsg.: Schwarz, M. ; Harfmann, J. (2017)
Investigation of the Action Sequence of Pilots during Landing using Markov Models.
EAAP Conference. Cascais, Portugal (26.-30.09.2016)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

This paper investigates the human impact on the strain of a landing gear during touchdown by exploring the action sequence taken by pilots. Forty-four trained, male pilots operated a landing maneuver in a flight simulator. Thirty flight parameters and personal data, like qualification and flight experience, were assessed. A Markov model was derived to identify typical action patterns and relate them to the resulting strain. Though identified patterns did not statistically significantly relate to the resulting strain, within four states of the Markov model predictors for the resulting strain were found. The findings could be used to develop assistance systems that react to uncommon action patterns by giving specific warnings to reduce the resulting strain on the landing gear.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Herausgeber: Schwarz, M. ; Harfmann, J.
Autor(en): Oberle, Marius ; König, Christina ; Bruder, Ralph
Art des Eintrags: Bibliographie
Titel: Investigation of the Action Sequence of Pilots during Landing using Markov Models
Sprache: Englisch
Publikationsjahr: 2017
Ort: Groningen,NL
Buchtitel: Proceedings of the 32nd Conference of the European Association for Aviation Psychology
Veranstaltungstitel: EAAP Conference
Veranstaltungsort: Cascais, Portugal
Veranstaltungsdatum: 26.-30.09.2016
Kurzbeschreibung (Abstract):

This paper investigates the human impact on the strain of a landing gear during touchdown by exploring the action sequence taken by pilots. Forty-four trained, male pilots operated a landing maneuver in a flight simulator. Thirty flight parameters and personal data, like qualification and flight experience, were assessed. A Markov model was derived to identify typical action patterns and relate them to the resulting strain. Though identified patterns did not statistically significantly relate to the resulting strain, within four states of the Markov model predictors for the resulting strain were found. The findings could be used to develop assistance systems that react to uncommon action patterns by giving specific warnings to reduce the resulting strain on the landing gear.

Freie Schlagworte: Markov Model, Landing Maneuver, Uncertainty, Human-Machine Interaction, Human Error
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Arbeitswissenschaft (IAD)
DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 805: Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus
Hinterlegungsdatum: 21 Nov 2016 12:30
Letzte Änderung: 04 Aug 2020 11:59
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