SOURCE-LINKED INTELLIGENCE

Terminal Airspace Digital Assistant

CORDIS · observation · Publication date unknown

thered through this interaction is currently barely used beyond the immediate information update cycles and possibly post ops investigations. This wealth of big-data,together with the introduction of machine learning (ML) algorithms that will learn to predict patterns and ATC instructions can be taken advantage of much more to improve capacity, efficiency and safety by providing decision making support to ATCOs and delegation of certain tasks. A digital assistant and corresponding HMI will be developed through TADA and AMAN will benefit from an improvement through the use of the same data and ML. TADA will be carried out by a consortium of 6 partners from 6 different EU countries including academia, ANSP, ATM system provider and an expert company in AI, bringing complimentary academic, technical, human factors and operational skills and expertise to the project. air traffic control, support to decision making, digital assistant, machine learning, eXplainable Artificial Intelligence, terminal airspace, arrival manager, real time simulation

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recordType

award

status

SIGNED

region

EU

value

1769978.75

unit

EUR