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ASTRA

Financiado

Cerrado

AI-enabled tactical FMP hotspot prediction and resolution

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 flig... ver más

28/02/2026

UNIVERSITY OF MALT...

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

UNIVERSITA TA MALTA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-09-01

HORIZON-SESAR-2022-DES-ER-01-WA2-5: ATM application-oriented Research f... ExpectedOutcome:Project results are expected to contribute to the following expected outcomes.

I+D

Cerrada hace 2 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

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UNIVERSITY OF MALTA

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Duración del proyecto: 29 meses Fecha Inicio: 2023-09-01
Fecha Fin: 2026-02-28

Líder del proyecto

UNIVERSITA TA MALTA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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