Abstract
This paper shows studies for the development of a mathematical model that adequately represents a pilot behavior in the specific task of offset landing, using data-driven modeling techniques. Flight test data was used for the identification procedure. Considerations on the pilot’s cognitive process and mathematical modeling possibilities were discussed to select the most appropriate inputs and outputs for the model. This data was used to identify the model using artificial neural network techniques. The models obtained were validated against the identification data and different data not used in the training process to evaluate the quality of the models. Conclusions include the difficulties of showing the generalization capabilities of those non-linear models and further studies.
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Acknowledgements
This study is partially supported by the National Council of Scientific and Technologic Development of Brazil (CNPq) under Grant 150238/2017-7.
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Turetta, F.M.S., Ayala, H.V.H., Trabasso, L.G., Coelho, L.S., Alfredson, J. (2018). Data-Driven Pilot Behavior Modeling Applied to an Aircraft Offset Landing Task. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2017. Advances in Intelligent Systems and Computing, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-60441-1_12
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DOI: https://doi.org/10.1007/978-3-319-60441-1_12
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