Analysing the Integration of AI Transformers to Pilot Assistance and Flight Simulation Environment

The aviation industry has increasingly leveraged artificial intelligence (AI) to enhance pilot performance, flight safety, and training efficiency. Among emerging AI technologies, Transformer-based models have shown exceptional capabilities in understanding complex sequences, processing large volumes of data, and generating predictive insights. In the context of pilot assistance and flight simulations, AI Transformers can analyze flight parameters, environmental conditions, and pilot behavior in real-time to provide intelligent decision support. They enable adaptive simulation scenarios, realistic virtual training environments, and predictive risk assessment, allowing pilots to practice emergency procedures and optimize decision-making under varied conditions. By integrating natural language processing, these models can also facilitate intuitive interaction between pilots and cockpit systems. This abstract explores the role of AI Transformers in modern aviation training and operational support, highlighting their potential to improve safety, efficiency, and the overall effectiveness of pilot training programs.

AI-Transformer, ASFT-Transformer framework, ANOVA-SVM, Long Short-Term Memory (LSTM), Large language Models (LLMs), Pilot Assistance systems, Flight Simulator

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