​This project aimed at gaining more insight into the mechanisms of pilot SD and LESA occurrence, capturing their dynamic fingerprint, and developing on-board intelligent schemes capable of predicting and detecting these dangerous phenomena associated to pilot behaviors.
Project Details
Findings: Final report submitted 9/24. Each of the mathematical models showed good capabilities of estimating each of the pilot parameters and represent a promising tool towards the characterization of pilot behavior using learning components. Continuation can be pursued by generalizing or extending the proposed results to other aircraft-pilot dynamics, possibly eVTOLs for AAM.
Student and Curriculum impact. The simulation and testing tools will be integrated as part of the experiential learning of the course AE623 Guidance, Navigation and Control that will be taught by the PI next Fall 2025. The proposed technique also allowed a master student in Aerospace Engineering to complement and enhance her thesis outcomes.​
Research Team
Principal Investigators
