Flight crew diagnostic using aviation simulator training data

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Abstract

This paper describes a new concept of flight crew assessment based on flight simulators training result. It is based on representation of pilot gaze movement with the aid of continuous-time Markov processes with discrete states. Considered are both the procedure of model parameters identification provided with goodness-of-fit tests in use and the classifier-building technique, which makes it possible to estimate degree of correspondence between the observed gaze motion distribution under study and reference distributions identified for different diagnosed groups. The final assessing criterion is formed on the basis of integrated diagnostic parameters, which are determined by the parameters of the identified models. The article provides a description of the experiment, illustrations, and results of studies aimed at assessing the reliability of the developed models and criteria, as well as conclusions about the applicability of the approach, its advantages and disadvantages.

General Information

Keywords: eye tracking, Markov model, multifactor Markov network, diagnostics, flight simulator, factor analysis

Journal rubric: Psychology of Labor and Engineering Psychology

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2016090310

For citation: Kuravsky L.S., Marmalyuk P.A., Yuryev G.A., Belyaeva O.B., Prokopieva O.Y. Flight crew diagnostic using aviation simulator training data. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2016. Vol. 9, no. 3, pp. 118–137. DOI: 10.17759/exppsy.2016090310. (In Russ., аbstr. in Engl.)

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Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, Dean of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-3375-8446, e-mail: l.s.kuravsky@gmail.com

Pavel A. Marmalyuk, PhD in Engineering, Head of the Laboratory of Psychology and Applied Software, Moscow State University of Psychology & Education, associate professor, Department of Information Technologies, Moscow State University of Psychology & Education, Moscow, Russia, e-mail: ykk.mail@gmail.com

Grigory A. Yuryev, PhD in Physics and Matematics, Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

O. B. Belyaeva, Student, Computer Science Faculty, Moscow State University of Psychology and Education, e-mail: olga95259@yandex.ru

O. Y. Prokopieva, Master student, Computer Science Faculty, Moscow State University of Psychology and Education, e-mail: prokopyeva08@mail.ru

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