Air traffic control
MAHALO: Modern ATM via Human/Automation Learning Optimisation
Supporting the transition to higher levels of automation in aviation by creating and empirically evaluating next generation computer-based tools
In the emerging age of Artificial Intelligence and Machine Learning, the MAHALO SESAR Exploratory Research project aims to answer simple, yet profound questions: should we be developing automation that is conformal to the human, or should we be developing automation that is transparent to the human? Do we need both? Further, are there tradeoffs / interactions between the concepts, in terms of air traffic controller trust, acceptance, or performance?
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