Artificial Intelligence in Pilot Training and Education – Towards a Machine Learning Aided Instructor Assistant for Flight Simulators

Publication Type:
Conference Proceeding
HCI International 2021 - Posters, 2021, 1420, pp. 581-587
Issue Date:
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The aviation industry was set to see unprecedented growth over the next two decades. Key occupations predicted to be in shortage included not only pilots, but also flight instructors. Undoubtedly, Covid-19 is currently having a huge impact on the industry. Nevertheless, the current environment further strengthens the need for pilots to maintain their training. Consequently, there is pressure to deliver high-quality training outcomes for an increasing number of pilots and trainees with limited resources available. Current simulator-based training schemes are limited by placing a significant reliance on the personal experience of flight instructors to assess pilot performance. Finding ways to increase the quality and efficiency of simulator-based training is therefore of high importance. With recent advances in artificial intelligence, it is possible to use machine learning techniques to extract latent patterns from massive datasets, to analyze pilot trainees’ activities, and to provide feedback on their performance by processing hundreds of different parameters available on flight simulators. An ML-aided pilot training and education framework is needed that exploits the power of the ML techniques for more objective performance evaluation. In this paper, we describe a conceptual framework for such a system and outline steps toward the development of a full digital instructor system with the potential to overcome current limitations and enabling comprehensive and meaningful feedback that is tailored to the individual need of the trainee.
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