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| Funder | European Commission |
|---|---|
| Recipient Organization | Collins Aerospace Ireland, Limited |
| Country | Ireland |
| Start Date | Jun 01, 2023 |
| End Date | May 31, 2026 |
| Duration | 1,095 days |
| Number of Grantees | 20 |
| Roles | Third Party; Participant; Coordinator |
| Data Source | European Commission |
| Grant ID | 101114692 |
The fast penetration of automation and Artificial Intelligence (AI) is boosting the adoption of autonomous systems across industries. Known as digitalisation, this trend is also rapidly changing aviation.
Indeed, driven by the increasing complexity of the entire aviation ecosystem (aircraft, air traffic control – ATC, airports), digitalisation provides solutions in the form of Digital Assistants (DAs) that, by teaming with their human counterparts (pilots, ATC operators, airport operators), support the execution of tasks to ensure safe and profitable operations in complex scenarios.
JARVIS Consortium – led by Collins Aerospace – aims at developing and validating three ATM solutions: an Airborne DA (AIR-DA, TRL4), an ATC-DA (TRL4), and an Airport DA (AP-DA, TRL6).
The AIR-DA will increase the level of automation in the flight deck and thanks to AI-based actions will act as enabler towards reduced crew operations and single pilot operations.
The adoption of the AIR-DA will allow pilots to deal with complex scenarios without compromising safety, security, while reducing the pilot workload.
The ATC-DA will increase the level of automation in control towers, where environmental KPIs and the capacity management of airspace will benefit from the adoption of AI-based technologies.
Finally, the AP-DA will increase the level of automation in airports, enhancing safety and security for intrusion detection scenarios.
The adoption of AI-driven technologies in the aviation ecosystem represents an appealing concept but entails challenges.
JARVIS will address key challenges common to the three different DAs: i) assured AI design, to deliver trustworthy, explainable, safe, and ethical decision-making algorithms; ii) Human AI Teaming, to deliver human-centric designs to maximise the teamwork between humans and autonomous systems; iii) big data and cloud infrastructures for the proper management of data moving from a centralised architecture to a more edge-to-cloud architectures.
Centro de Referencia Investigacion Desarrollo E Innovacion Atm, A.I.E.; Athens International Airport S.A.; Stichting Koninklijk Nederlands Lucht - En Ruimtevaartcentrum; Swedavia Ab; Deep Blue Srl; Enav Spa; Enaire; Eurocontrol - European Organisation for the Safety of Air Navigation; Nextant Applications & Innovative Solution Srl; Boeing Aerospace Spain; Deutsches Zentrum Fur Luft - Und Raumfahrt Ev; Indra Sistemas Sa; Rockwell Collins France Sas; Airbus Defence and Space Sas; Advanced Laboratory On Embedded Systems Srl; C.I.R.A. Centro Italiano Ricerche Aerospaziali Scpa; Indra Factoria Tecnologica Sl; Leonardo - Societa Per Azioni; Ecole Nationale de L Aviation Civile; Collins Aerospace Ireland, Limited
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