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TRIMIS

Towards an Automated and exPlainable ATM System

TAPAS

Towards an Automated and exPlainable ATM System

Call for proposal: 
H2020-SESAR-2019-2
Link to CORDIS:
Objectives: 

As Artificial Intelligence (AI) becomes an increasing part of our lives in general, individuals are finding that the need to trust these AI based systems is paramount. Air Traffic Management (ATM) is not an stranger to this: with a system close to, or already at, a saturation level, AI applications are considered a main enabler to reach higher levels of automation.

This would mean a fundamental shift in the automation approach when moving from the classical human-machine interaction to a potentially much richer solution enabled by these AI systems, in which trust in the operations needs to be generated. As humans, operators must be able to fully understand how decisions are being made so that they can trust the decisions of AI systems. The lack of explainability and trust hampers the ability (both individual and global) to fully trust AI systems.

TAPAS aims at exploring highly automated AI-based scenarios through analysis and experimental activities applying eXplainable Artificial Intelligence (XAI) and Visual Analytics, in order to derive general principles of transparency which pave the way for the application of these AI technologies in ATM environments, enabling higher levels of automation.

Specifically, TAPAS will:

• Analyse two operational environments: ATC (Air Traffir Control) Conflict Detection & Resolution (tactical), and Air Traffic Flow Management (pre-tactical). For them, levels of automation 1 to 3 according to SESAR Model will be considered.

• Develop eXplainable Artificial Intelligence (XAI) prototypes addressing the requirements and acceptability criteria of the scenarios.

• Run experiments that assess the applicability of these XAI modules in the higher levels of automation considered, exploring different ways of interaction and information exchange.

• Apply Visual Analytics techniques to contribute to explainability of decissions.

• Extract conclusions, principles and recommendations related to transparency of AI in ATM.

Institution Type:
Institution Name: 
European Commission
Type of funding:
Lead Organisation: 

Centro De Referencia Investigacion Desarrollo E Innovacion Atm, A.i.e.

Address: 
Avda De Aragon 402 4 Edificio Allende
N/A Madrid
Spain
EU Contribution: 
€212,750
Partner Organisations: 

Fraunhofer Gesellschaft Zur Foerderung Der Angewandten Forschung E.v.

Address: 
HANSASTRASSE 27C
80686 MUNCHEN
Germany
EU Contribution: 
€174,100

Boeing Research & Technology Center

Address: 
Cañada Real de las Merinas 1-3, Edificio 4
28042 MADRID
Spain
EU Contribution: 
€156,241

Indra

Address: 
Avenida de Bruselas, 35
Alcobendas Madrid
Spain
EU Contribution: 
€128,625

University Of Piraeus Research Center

Address: 
Gr. Lampraki 122
185 32 Piraeus
Greece
EU Contribution: 
€162,250

Isa Software

Address: 
St Georges House Chester Road 215-219
Manchester
M154JE
United Kingdom
EU Contribution: 
€163,444
Technologies: 
Development phase:
Development phase: