Descrizione del progetto
La trasformazione digitale della gestione del trasporto aereo
La gestione del trasporto aereo (ATM, Air transport management) richiede la collaborazione delle compagnie aere, dei fornitori di servizi e delle autorità di terra per garantire operazioni quotidiane senza intoppi. Grazie ai progressi della tecnologia e alla digitalizzazione dei servizi, l’analisi dei megadati e le nuove metodologie di valutazione del rischio possono rivelarsi utili. Il progetto SafeOPS, finanziato dall’UE, studierà in che modo questi servizi possano contribuire a migliorare la sicurezza e l’efficienza dei costi delle operazioni di trasporto per via aerea. Particolare attenzione sarà rivolta al processo decisionale in scenari go-around di grande rilevanza per la sicurezza sia per le compagnie aeree che per i fornitori di servizi di navigazione aerea nella gestione ATM. In generale il progetto promuoverà la modernizzazione dell’ATM basata su strumenti di intelligenza artificiale e dedicherà una speciale attenzione alle interazioni tra esseri umani (controllori).
Obiettivo
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.
Campo scientifico
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
80333 Muenchen
Germania