Intent-Based Mode-Confusion Detection (Learning-based)
- Detailed mathematical models of the autopilot and flight management system logics with known system parameters are difficult to obtain
- An intent-based Generalized Fuzzy Hidden Markov Model (GFHMM) using a Viterbi-like algorithm is developed to learn model parameters for mode confusion detection
Proposed Architecture
Proposed Architecture
Demonstration
Demonstration
- Demonstrated with data of ~600 flights generated by the Multi-Aircraft Control System (MACS)
- Illustrative Example
Vertical Profile
Zoomed-in view from 60 sec to 150 sec
Inferred intents (top: automation; middle: pilot) and detected mode confusion (bottom)
Related Publication
Related Publication
- H. Lyu, J.S. Nandiganahalli, S. Lee, and I. Hwang, “Automation Intent Inference Using the GFHMM for Flight Deck Mode Confusion Detection,” AIAA Journal of Aerospace Information Systems, Vol. 15, No. 3 (2018), pp. 172-177.