MAHALO project
MAHALO project researches how to improve air traffic management with automated systems that respect human operators. It uses AI and machine learning to explore automation that is either conformal to the human or transparent to the human, evaluated through empirical studies with air traffic controllers. The project operates as a SESAR Exploratory Research initiative, focusing on the core technology of human-in-the-loop automation and its integration into ATM workflows. It targets aviation stakeholders and research partners, and examines trust, acceptance, and performance tradeoffs. The work aims to advance the scalability and effectiveness of future ATM systems by clarifying how automation should interact with human operators.
MAHALO project
MAHALO project researches how to improve air traffic management with automated systems that respect human operators. It uses AI and machine learning to explore automation that is either conformal to the human or transparent to the human, evaluated through empirical studies with air traffic controllers. The project operates as a SESAR Exploratory Research initiative, focusing on the core technology of human-in-the-loop automation and its integration into ATM workflows. It targets aviation stakeholders and research partners, and examines trust, acceptance, and performance tradeoffs. The work aims to advance the scalability and effectiveness of future ATM systems by clarifying how automation should interact with human operators.