Imagine an airport where planes are moved by robotic tugs instead of their own engines to save fuel. To prevent traffic jams, an AI acts like a super-smart air traffic controller on the ground, timing every move perfectly. It works side-by-side with human operators, handling the routine steering while letting people step in for complex decisions.
Airport ground operations rely on human operators who face high workloads and struggle to optimize taxiing routes. This leads to departure delays and wasted fuel, especially as the number of vehicles increases due to the introduction of towing tugs.
A support tool for automated ground operations supervision featuring adaptive AI algorithms for conflict-free routing and speed management of aircraft and tugs.
If you are a ground service provider dealing with inefficient aircraft movement and high fuel waste — this project developed AI-driven routing and speed management that optimizes the flow of autonomous tugs. This increases ground capacity and reduces the environmental footprint of taxiing.
If you are an airport operator dealing with departure delays and human operator overload — this project developed a support tool for automated ground operations supervision. It allows AI to give clearances and manage routes, reducing the workload on ground controllers.
If you are a vehicle manufacturer dealing with the need for smarter fleet coordination — this project developed adaptive AI algorithms for engine-off taxiing. This enables your tugs to integrate into a conflict-free, automated airport ecosystem.
Based on available project data, specific pricing or implementation costs are not provided.
The project specifically targets major European airports to increase ground traffic capacity and manage complex engine-off taxiing operations.
Based on available project data, there is no specific information regarding IP or licensing terms.
The system uses human-centered design and adaptive AI to match the operator's way of working, ensuring a seamless partnership where humans can supervise and take over automation.
The project period runs from 2023-09-01 to 2026-02-28, suggesting the development and validation phase ends in early 2026.
The consortium is lean and highly specialized, consisting of 5 partners across 4 countries. With a 40% industry ratio (including 1 SME), the project balances academic research from 2 universities and 1 research center with practical industrial application, led by the Ecole Nationale de l'Aviation Civile.
Contact the Ecole Nationale de l'Aviation Civile (ENAC) in France.
Contact us to find out how to integrate ASTAIR's AI routing into your ground operations.
