Project description
AI supporting air traffic controllers
Air traffic controllers help planes land at increasingly busy airports. They need to keep planes as close together as safely possible to maintain capacity. The EU-funded ORCI project aims to use AI solutions to boost runway throughput and efficiency, especially during periods of medium to very high traffic density. The project plans to develop an advanced automation tool for terminal manoeuvring areas. This tool will be based on an AI model trained on surveillance data and other data derived from air traffic control voice communications between pilots and controllers. The project will ultimately demonstrate and validate this solution, potentially revolutionising efficiency and performance in air traffic management
Objective
ORCI will explore innovative AI-based solutions to help increase runway throughput using advanced automation support tools in the TMA domain. Specifically, the objective is to provide key information to Air Traffic Controllers in final approach sectors, to support informed decisions on when to issue vectoring instructions to aircraft for optimal spacing between consecutive arrivals during medium, high, very high-density and increasingly complex TMA airspace operations.
To achieve this objective, the project will develop an AI model that is trained using radar surveillance data and ATC voice communications between pilots and controllers.
During the project, Barcelona and Lisbon approach operations will be assessed. This will include interviews with ATCO experts from the respective ANSP partners, as well as in-depth analysis of local arrival characteristics (e.g. geometries, procedures, etc.). In addition, high amounts of radar surveillance and voice communications data will be collected and processed, to support and guide the training and testing of the AI models.
The validation of the AI model will be supported by Human in the loop and Fast Time simulation techniques (using the RAMS Plus tool) to ensure that the performance of the AI model is evaluated in a realistic and controlled environment, and to get some initial human performance and safety related feedback.
The successful implementation of the AI model is anticipated to optimize delivery of vectoring instructions, leading to enhanced capacity, efficiency, environmental performance, and overall improvements to arrival air traffic management that are consistent with SESAR performance targets. Additional benefits also extend to optimization of the runway throughput by reducing both ATC workload and the potential for human error. The expected solution could also be extended to incorporate the use of time-based separation for arrivals and digitally shared trajectory information coming from the flight-deck
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- social sciences sociology industrial relations automation
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering telecommunications radio technology radar
- social sciences social geography transport transport planning air traffic management
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.5 - Climate, Energy and Mobility
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-JU-RIA - HORIZON JU Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-SESAR-2023-DES-ER-02
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
75003 PARIS
France
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.