AI Algorithms for Dynamic Maneuver Clustering and Classification in Flight Training

This work investigates the application of Artificial Intelligence (AI) algorithms for dynamic maneuver clustering and classification in the context of flight training. The increasing demand for pilots necessitates innovative training methods, and AI offers the potential to enhance training efficiency and efficacy. This research focuses on comparing and contrasting unsupervised (clustering) and supervised (classification) algorithms to identify and assess student pilots’ maneuvers. Using data generated from Monte Carlo simulations with a random walk to emulate student flight data, this study evaluates the performance of various AI algorithms. Preliminary results demonstrate the potential of these algorithms for accurately clustering and classifying flight maneuvers, laying the groundwork for developing AI-powered flight training systems. This research highlights the significance of AI in addressing the challenges of pilot training and contributes to the advancement of AI applications in aviation education