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Experimental Psychology (Russia)

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2072-7593

ISSN (online): 2311-7036

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

License: CC BY-NC 4.0

Started in 2008

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Assessing the Aircraft Crew Actions with the Aid of a Human Factor Risk Model 53

Kuravsky L.S.
Doctor of Engineering, 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

Yuryev G.A.
PhD in Physics and Matematics, Associate Professor, Head of Scientifi c Laboratory, Moscow State University of Psychology & Education, Moscow, Russia
ORCID: https://orcid.org/0000-0002-2960-6562
e-mail: g.a.yuryev@gmail.com

Zlatomrezhev V.I.
Head of Laboratory, State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia
ORCID: https://orcid.org/0000-0003-1776-6881
e-mail: vizlatomr@2100.gosniias.ru

Yuryeva N.E.
PhD in Engineering, Research Fellow, Information Technology Center for Psychological-Ecological Studies of the Faculty Newsletter-Technologies, Research Associate, Moscow State University of Psychology and Education, Moscow, Russia
ORCID: https://orcid.org/0000-0003-1419-876X
e-mail: yurieva.ne@gmail.com

Abstract
Presented is a human factor risk model when piloting an aircraft. This model is based on comparing representations of the evaluated crew actions with the comparable action representations of various types and performance quality, which form a representative sample and are contained in a pre-formed specialized database. The risk in question is represented by probabilistic estimates, which result from consistent applications of the Principal Component Analysis, Multidimensional Scaling, and Cluster Analysis to three types of characteristics, viz.: parameters of flights and states of aircraft systems, gaze movement trajectories and time series of oculomotor activity primary indexes. These steps form the clusters of flight fragments for various types and performance quality, including abnormal ones. The Discriminant Analysis provides calculating the probabilistic profile for belonging to certain target clusters, with a final conclusion being derived from this structure. Key elements of the approach presented are three new metrics used to compare crew actions and to ensure significant discrimination for flight fragments of various types and performance quality. Detailing flight parameters contributions in differences of the flight fragments in a given metric is carried out to provide meaningful analysis of the detected abnormality causes. With sufficient computational performance, the flight data analysis under consideration can be implemented in real time automatic mode.

Keywords: human factor risk model, Principal Component Analysis, Multidimensional Scaling, Cluster Analysis, oculomotor activity indexes

Column: Psychology of Labor

DOI: https://doi.org/10.17759/exppsy.2020130211

A Part of Article

An objective assessment of the piloting performance is important for assessing the risks associated with the Information Management Field (IMF) of the cockpit, optimizing IMF and training the crews. One of the critical issues in this regard is the development of evaluation criteria.

For Reference

Acknowledgements

This work was performed as a part of the “SAFEMODE” Project (Grant Agreement No 814961) with the financial support of the Ministry of Science and Higher Education of the Russian Federation (Project UID RFMEFI62819X0014).

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