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AI-enabled tactical FMP hotspot prediction and resolution

Project description

A new tool for air traffic management

Air traffic congestion continues to challenge the aviation industry despite the implementation of air traffic flow and capacity management (ATFCM) measures. Based on flight plan data, these measures fail to consider actual aircraft trajectories. Consequently, air traffic controllers (ATCOs) are left with limited time to resolve hotspots, causing delays and increased workload. In this context, the EU-funded ASTRA project aims to develop an AI-based tool that predicts and resolves hotspots much earlier than current methods allow. Specifically, flow management position (FMP) personnel will gain the ability to predict hotspots at least one hour ahead and propose resolution strategies. With improved capacity, adherence to efficient trajectories, reduced ATCO workload, and predictable operations, the benefits of this tool are significant.


Various Air Traffic Flow and Capacity Management (ATFCM) measures are implemented during the pre-tactical and tactical flow management phases to resolve traffic congestion (aka hotspots); however, these are generally based on flight plan data. On the day of operation, an aircraft's actual trajectory may differ significantly from its flight plan and, as a result, hotspots still occur and these have to be resolved by Air Traffic Controllers (ATCOs) without sufficient advance notice. With today's ATFCM tools, tactical Air Traffic Control (ATC) hotspots are only identified up to around 20 minutes in advance. The aim of ASTRA is to bridge the gap between the Flow Management Position (FMP) and the planner Controller Working Position (CWP) by developing a AI-based tool (to TRL2) for FMP personnel which can predict and resolve hotspots earlier than today, before they are within the scope of the sector planner. The objectives of the project are to: (a) develop an FMP function to predict hotspots at least 1 hour in advance, and to propose strategies to resolve them; (b) develop Human Machine Interface (HMI) concepts to allow interaction between operators and the tool; and (c) demonstrate and validate the tool by conducting human-in-the-loop Real-Time Simulations (RTS) in a representative operational environment. The benefits of this tool would include: increased capacity at ATC unit level; better adherence to efficient and green business trajectories; reduced ATCO workload; and more predictable operations. The project will be carried out by a multidisciplinary consortium of 5 partners from 4 countries - Malta, Spain, Italy and Switzerland - including an academic institution, an ANSP, an Air Traffic Management (ATM) technology provider, and two consulting/research entities. The partners are complementary to each other and bring a combination of academic, technical, human factor and operational skills and expertise to the project.


Net EU contribution
€ 343 682,00
2080 MSIDA

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Malta Malta Malta
Activity type
Higher or Secondary Education Establishments
Total cost
€ 343 682,50

Participants (2)

Partners (2)