Authors :
Alain Philippe Gruchet
Volume/Issue :
Volume 10 - 2025, Issue 11 - November
Google Scholar :
https://tinyurl.com/zk6rnv8z
Scribd :
https://tinyurl.com/3dbwj9ed
DOI :
https://doi.org/10.38124/ijisrt/25nov1253
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Abstract :
Flight simulators have long been essential in aviation training, yet their reliance on preprogrammed scenarios
and fixed difficulty levels limits realism and adaptability. Recent advances in cyber-physical systems and digital twins
introduce a new generation of simulators capable of synchronizing with real-world flight data, integrating biometric
monitoring, and creating immersive VR/AR environments. These technologies allow training scenarios to reflect actual
operational risks, personalize exercises to individual pilot profiles, and enhance preparation for rare abnormal events. A
patented cyber-physical simulator that transforms real flight telemetry into dynamic training modules exemplifies this
direction. By merging data-driven modeling with immersive visualization, cyber-physical simulators and digital twins
establish a more adaptive, safe, and effective approach to pilot training.
Keywords :
Cyber-Physical Systems; Digital Twin; Flight Simulator; Aviation Training; VR/AR; IoT; Big Data; Abnormal Scenarios.
References :
- Ayaz, H., & Dehais, F. (2019). Neuroergonomics: The Brain at Work in Everyday Life. Academic Press. DOI: 10.1016/C2017-0-02037-4
- Boeing. (2023). Pilot and Technician Outlook 2023–2042. Retrieved from https://www.boeing.com/commercial/market/pilot-technician-outlook
- Glaessgen, E., & Stargel, D. (2012). The digital twin paradigm for future NASA and U.S. Air Force vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. DPI: 10.2514/6.2012-1818
- Kluge, A., Sauer, J., Schüler, K., & Burkolter, D. (2020). Designing training for complex systems using a digital twin. Applied Ergonomics, 88, 103154. DOI: doi.org/10.1016/j.apergo.2020.103154
- Qiao, Y., Zhao, Z., & Xu, J. (2021). Human digital twins for personalized pilot training in cyber-physical systems. IEEE Access, 9, 55678–55690. DOI: 10.1109/ACCESS.2021.3070352
- Sheridan, T. B. (2019). Human–automation interaction: Introduction. Annual Review of Control, Robotics, and Autonomous Systems, 2, 1–16. DOI: 10.1146/annurev-control-053018-023617
- Strohkorb Sebo, S., et al. (2020). Interaction with autonomous systems: Training for supervisory roles. Frontiers in Robotics and AI, 7, 33. DOI: 10.3389/frobt.2020.00033
- Wickens, C. D., & McCarley, J. S. (2021). Applied Attention Theory. CRC Press. DOI: 10.1201/9781003137740
- Xu, C., Zhang, L., & Wang, T. (2022). Cyber-physical training platforms for aviation safety: From big data to adaptive learning. Journal of Aerospace Information Systems, 19(7), 300–315. DOI: 10.2514/1.I010967
Flight simulators have long been essential in aviation training, yet their reliance on preprogrammed scenarios
and fixed difficulty levels limits realism and adaptability. Recent advances in cyber-physical systems and digital twins
introduce a new generation of simulators capable of synchronizing with real-world flight data, integrating biometric
monitoring, and creating immersive VR/AR environments. These technologies allow training scenarios to reflect actual
operational risks, personalize exercises to individual pilot profiles, and enhance preparation for rare abnormal events. A
patented cyber-physical simulator that transforms real flight telemetry into dynamic training modules exemplifies this
direction. By merging data-driven modeling with immersive visualization, cyber-physical simulators and digital twins
establish a more adaptive, safe, and effective approach to pilot training.
Keywords :
Cyber-Physical Systems; Digital Twin; Flight Simulator; Aviation Training; VR/AR; IoT; Big Data; Abnormal Scenarios.