AI4HyDrop
Financiado
An AI based Holistic Dynamic Framework for a safe Drone s Operations in restrict...
An AI based Holistic Dynamic Framework for a safe Drone s Operations in restricted and urban areas
With an increasing number and diversity of potential drone operations, managing the airspace to accommodate these drones will become an increasingly sophisticated task, especially in densely populated urban areas encompassing rest...
With an increasing number and diversity of potential drone operations, managing the airspace to accommodate these drones will become an increasingly sophisticated task, especially in densely populated urban areas encompassing restricted zones with dynamic environmental and operational influences. Due to the associated higher probability of conflicts, and ultimately collisions, such areas require management of dedicated structured airspace, operations, and services to help mitigate these potential hazards.
Several projects are currently working on defining ConOps for U-space services. Corus and Corus-XUAM have defined a possible capabilities model, such as airspace organization and services. However, a holistic framework is necessary to create an effective and efficient flow of information between the various capabilities in order to systematically organise the airspace usage. Such an automated Air Traffic Management System will be essential for the introduction drone operations at scale.
AI4HyDrop evaluates the various stakeholder needs, delivering validated concepts, defining a methodology for an airspace structure organisation and associated U-space services. The framework considers the information from other services such as meteorological and separation provision, which can then be used for flight planning approval process, prioritization. In addition, essential elements such as surveillance and contingency planning can be addressed. The framework incorporates various AI based tools and associated information flows necessary to addresses the complexity, safety and scalability required for implementing such U-space services.
The proposed framework represents a digital step change in ATM, using AI as a means to overcome many critical barriers foreseen in the introduction of automated U-space services. The findings could later be expanded to support general airspace management.
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Duración del proyecto: 32 meses
Fecha Inicio: 2023-06-08
Fecha Fin: 2026-02-28
Fecha Fin: 2026-02-28
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-06-08
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
UNIVERSITETET I SOROST-NORGE
No se ha especificado una descripción o un objeto social para esta compañía.
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