AI Situational Awareness Foundation for Advancing Automation

Informazioni relative al progetto

AISA

ID dell’accordo di sovvenzione: 892618

DOI

10.3030/892618

Progetto chiuso

Data della firma CE 23 Aprile 2020

Data di avvio 1 Giugno 2020

Data di completamento 30 Novembre 2022

Finanziato da

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Costo totale

€ 990 125,00

Contributo UE

€ 990 125,00

Coordinato da

SVEUCILISTE U ZAGREBU FAKULTET PROMETNIH ZNANOSTI
Croatia

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (7)

Risk assessment report
Final Project Results Report
Report on human-machine distributed SA

Report on humanmachine distributed SA

TRL-Assessment Report

TRLAssessment Report

Exploitation and Dissemination Report
Requirements for automation of monitoring tasks via AI SA
Concept of Operations for AI Situational Awareness System

Demonstrators, pilots, prototypes (1)

Proof-of-concept KG system

Open Research Data Pilot (1)

Data Management Plan

Data Management Plan according to the Open Research Data pilot

Other (6)

Facts, rules and queries capturing en-route ATC operations
4D trajectory prediction module
Populated knowledge graph
Conflict detection module
KG-Prolog mapper
Air traffic complexity estimation module

Websites, patent fillings, videos etc. (1)

Project’s website and factsheet

Pubblicazioni

Peer reviewed articles (2)

The Proposal of a Concept of Artificial Situational Awareness in ATC

Autori: Tomislav Radišić, Petar Andraši, Doris Novak, Tea Rogošić
Pubblicato in: Engineering Power - Bulletin of the Croatian Academy of Engineering, Numero Vol. 15(2) 2020, 2020, Pagina/e 23-28, ISSN 1331-7210
Editore: Croatian Academy of Engineering

Learning Assurance Analysis for Further Certification Process of Machine Learning Techniques: Case-Study Air Traffic Conflict Detection Predictor

Autori: Javier A. Pérez-Castán, Luis Pérez Sanz, Marta Fernández-Castellano, Tomislav Radišić, Kristina Samardžić, Ivan Tukarić
Pubblicato in: Sensors - Special Numero Sensors for Navigation and Control Systems, Numero 22(19), 7680, 2022, ISSN 1424-8220
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s22197680

Conference proceedings (4)

Design of an ATC Tool for Conflict Detection Based on Machine Learning Techniques

Autori: Javier Alberto Pérez-Castán, Luis Pérez-Sanz, Lidia Serrano-Mira, Francisco Javier Saéz-Hernando, Irene Rodríguez Gauxachs, Víctor Fernando Gómez-Comendador
Pubblicato in: Aerospace - Special Numero 11th EASN International Conference on Innovation in Aviation & Space to the Satisfaction of the European Citizens, Numero 9(2), 67, 2022, ISSN 2226-4310
Editore: MDPI
DOI: 10.3390/aerospace9020067

Creating an ATC knowledge graph in support of the artificial situational awareness system

Autori: Michael Schrefl, Bernd Neumayr, Sebastian Gruber, Marlene Hartmann, Ivan Tukarić, Tomislav Radišić
Pubblicato in: Transportation Research Procedia, Numero Volume 64, 2022, Pagina/e Pages 328-336, ISSN 2352-1465
Editore: Elsevier B.V.
DOI: 10.1016/j.trpro.2022.09.037

Novel Artificial Situational Awareness System is Comparable with Human Situational Awareness in the En-route Air Traffic Control Domain

Autori: Kristina Samardžić, Tomislav Radišić, Ivan Tukarić, Ruth Esther Häusler Hermann
Pubblicato in: Transportation Research Procedia, Numero Volume 64, 2022, Pagina/e Pages 316-327, ISSN 2352-1465
Editore: Elsevier B.V.
DOI: 10.1016/j.trpro.2022.09.036

Machine Learning classification techniques applied to static air traffic conflict detection

Autori: Javier A. Pérez-Castán, L. Pérez-Sanz, J. Bowen-Varela, L. Serrano-Mira, Tomislav Radisic, Thomas Feuerle
Pubblicato in: IOP Conference Series: Materials Science and Engineering, Numero Volume 1226, 2022, ISSN 1757-8981
Editore: IOP Science
DOI: 10.1088/1757-899x/1226/1/012019