DIALOG | Deciphering Intents of Air traffic controllers, workLOad assessment and Gaze analysis to enable their efficient and trustworthy collaboration with AI

Summary
The DIALOG project aims to improve collaboration between air traffic controllers (ATCOs) and artificial intelligence (AI) systems in air traffic management. It addresses a very ambitious goal of enabling AI members of human-AI teams to anticipate when and what kind of assistance their human teammates need and to respond on that. DIALOG will develop an AI-based digital assistant called Teamwork Assistant that uses speech recognition and understanding of pilot-controller exchanges to infer ATCOs' intent and goals. It also utilizes machine learning-based methods to assess ATCOs' workload and attention in real-time based on voice, physiology, and behavioral data. The actions of the digital assistant are determined based on the ATCOs' current state, attention allocation, traffic situation, and general context. The project will develop prototypes and conduct validation exercises in close collaboration with end-users to assess the performance and usability of the proposed solutions.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101166886
Start date: 01-09-2024
End date: 28-02-2027
Total budget - Public funding: 1 974 387,50 Euro - 1 974 387,00 Euro
Cordis data

Original description

The DIALOG project aims to improve collaboration between air traffic controllers (ATCOs) and artificial intelligence (AI) systems in air traffic management. It addresses a very ambitious goal of enabling AI members of human-AI teams to anticipate when and what kind of assistance their human teammates need and to respond on that. DIALOG will develop an AI-based digital assistant called Teamwork Assistant that uses speech recognition and understanding of pilot-controller exchanges to infer ATCOs' intent and goals. It also utilizes machine learning-based methods to assess ATCOs' workload and attention in real-time based on voice, physiology, and behavioral data. The actions of the digital assistant are determined based on the ATCOs' current state, attention allocation, traffic situation, and general context. The project will develop prototypes and conduct validation exercises in close collaboration with end-users to assess the performance and usability of the proposed solutions.

Status

SIGNED

Call topic

HORIZON-SESAR-2023-DES-ER2-WA2-4

Update Date

01-10-2024
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Horizon Europe
HORIZON.2 Global Challenges and European Industrial Competitiveness
HORIZON.2.5 Climate, Energy and Mobility
HORIZON.2.5.0 Cross-cutting call topics
HORIZON-SESAR-2023-DES-ER-02
HORIZON-SESAR-2023-DES-ER2-WA2-4 ATM application-oriented research for Artificial Intelligence (AI) for aviation