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From adaptive interfaces to cyber-physical systems: innovations transforming flight safety

Authors

Olivier Ferrari

Rubric:Technical sciences in general
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The rapid digitalization of aviation has redefined how pilots interact with flight systems, transitioning from manual control to highly automated and cognitively adaptive environments. Building on the foundations of adaptive human–machine interfaces and recent advances in neuroergonomics, this paper explores the continuum from adaptive cockpit design to the emergence of fully integrated cyber-physical systems (CPS) that redefine flight safety. Drawing on the pioneering works of Alain Philippe Gruchet, the study examines how adaptive visualization, psychophysiological monitoring, and cognitive modeling have evolved into closed-loop architectures capable of perceiving, reasoning, and acting in synchrony with the human operator. The discussion highlights three major shifts: from static to adaptive information display, from task-based to state-based automation, and from isolated systems to interconnected CPS networks. By synthesizing developments across avionics engineering, cognitive neuroscience, and safety certification, the paper identifies how these innovations collectively create a new paradigm of “human-aware” aviation technology.

Keywords

adaptive cockpit interface; cognitive ergonomics; neuroadaptive systems; cyber-physical systems (CPS); pilot monitoring; flight safety; human–machine interaction; artificial intelligence in aviation.

Authors

Olivier Ferrari

Rubric:Technical sciences in general
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References:

Aricò, P., Borghini, G., Di Flumeri, G., Colosimo, A., Bonelli, S., Golfetti, A., & Babiloni, F. (2016). Adaptive automation triggered by EEG-based mental workload index: A passive brain–computer interface application in realistic air traffic control environment. Frontiers in Human Neuroscience, 10 (539). https://doi.org/10.3389/fnhum.2016.00539

Berberian, B., Somon, B., Sahaï, A., & Gouraud, J. (2017). The out-of-the-loop brain: A neuroergonomic approach to human–automation interaction. Annual Reviews in Control, 44, 303–315.

Dehais, F., Lafont, A., Roy, R., & Fairclough, S. H. (2020). A neuroergonomics approach to mental workload, engagement and human performance. Frontiers in Neuroscience, 14 (268).

Fairclough, S. H., & Lotte, F. (2020). Grand challenges for physiological computing. Journal of Neural Engineering, 17 (5), 051001. https://doi.org/10.1088/1741-2552/aba3d2]

Huttner, J. P., Tews, L., Laudien, T., & Friedrich, M. (2024). Bridging the gap: Adaptive HMI innovations for next-gen fighter cockpits. Proceedings of the AIAA Scitech 2024 Forum.

Zander, T. O., & Jatzev, S. (2012). Context-aware brain–computer interfaces: Exploring the information space of user, technical system, and environment. Journal of Neural Engineering, 9 (1), 016011.

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