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SafeOPS

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Cerrado

From Prediction to Decision Support Strengthening Safe and Scalable ATM Servic...

From Prediction to Decision Support Strengthening Safe and Scalable ATM Services through Automated Risk Analytics based on Operational Data from Aviation Stakeholders Maintaining safety and cost-efficiency of air transport operations while increasing the capacity will push the next generation of ATM systems towards digitalization. In the mid-term, a digitalized system in the human operated ATM... ver más

31/12/2022

TUM

998K€

Presupuesto del proyecto: 998K€

Líder del proyecto

TECHNISCHE UNIVERSITAET MUENCHEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 5 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-12-31

SESAR-ER4-06-2019: Safety and Resilience

I+D

Cerrada hace 5 años

0% 100% 100%

Información adicional privada

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

5 Participantes

TUM

228.00K€ | Lider

DEEP BLUE

172.75K€ | Participante

IMDEA NETWORKS

223.25K€ | Participante

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Duración del proyecto: 26 meses Fecha Inicio: 2020-10-30
Fecha Fin: 2022-12-31

Líder del proyecto

TECHNISCHE UNIVERSITAET MUENCHEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 998K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Maintaining safety and cost-efficiency of air transport operations while increasing the capacity will push the next generation of ATM systems towards digitalization. In the mid-term, a digitalized system in the human operated ATM environment will be capable of delivering reliable predictive analytics based on automated information processing, providing decision support for human operators. SafeOPS supports these future services by investigating the use of big data analytics together with new risk assessment methodologies. ANSP and airlines are the relevant stakeholders of the aviation business, forming the SafeOPS consortium. Several research institutes complement the consortium. To ensure the high confidentiality levels of the associated datasets, SafeOPS utilizes DataBeacon, a platform that allows fusing and analyzing confidential aviation data. As an exemplary safety-critical scenario, SafeOPS considers go-arounds that are of high safety relevance for both, airlines and ANSPs. Based on successful unstable approach predictions, developed in the Horizon2020 project SafeClouds.eu, SafeOPS will carry out go-around predictions and analyze their impact onto the safety and resilience of ATM in detail. As recognized by the SESAR Single Programming Document, data-driven and machine learning technologies are a cost-efficient asset to reduce current fragmentation and upgrade inefficient old technologies. In turn, they introduce new challenges for ATM stakeholders, from controllers and their training to regulators and certification agencies. SafeOPS addresses some of these challenges by fostering the ATM modernization based on AI tools with an application on safety and resilience through an exemplary case study. It puts a special focus on the interaction among humans (controllers) and within the socio-technical system under the influence of this breakthrough technology. Therefore, it addresses both key performance areas from the Safety and Resilience ATM Master Plan.

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