Imagine a smart co-pilot for air traffic controllers that learns from years of past decisions to suggest the best moves in real-time. It's like a GPS for airport airspace that predicts traffic jams before they happen and suggests the smoothest path for planes to land. This helps controllers handle crowded skies with less stress and more precision.
Air traffic controllers at busy airport hubs are overwhelmed by complex data, and the valuable historical data they generate is currently wasted. This leads to underutilized airspace capacity and potential safety risks.
An AI digital assistant and a new human-machine interface (HMI) that uses machine learning to suggest ATC actions and improve arrival sequencing.
If you are an ANSP dealing with congested terminal airspace at major hubs — this project developed an AI digital assistant that uses historical controller data to improve capacity and safety.
If you are an ATM system provider dealing with outdated arrival management tools — this project developed ML-based insights to enhance Arrival Manager (AMAN) sequences for better trajectory efficiency.
If you are a consulting firm dealing with high controller workload and stress — this project developed a new human-machine interface (HMI) that optimizes how AI and humans team up in ATC.
Based on available project data, no pricing or specific EU contribution amounts are provided.
The project specifically targets Terminal Airspace (TMA) and multi-airport hubs, suggesting it is designed for high-density traffic environments.
Based on available project data, the IP and licensing terms are not specified, though it involves a consortium of 6 partners including SMEs and industry.
It is designed to integrate with and enhance the Arrival Manager (AMAN) tool and the broader Air Traffic Management (ATM) system.
The project runs from 2024-09-01 to 2027-02-28, with the AI tool expected to be fully developed by April 2026.
The consortium is heavily industry-driven with an 83% industry ratio, consisting of 6 partners across 5 countries. The presence of 3 SMEs, an ANSP, and an ATM system provider indicates a strong focus on commercial viability and operational integration rather than purely academic research.
Contact INNOVACION Y GESTION EN NAVEGACION AEREA SL in Spain
Contact us to explore integration opportunities with the TADA AI assistant.
