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Uncertainty in avionics analytics ontology for decision-making support

Insaurralde, C. C.; Blasch, E.


E. Blasch


With the growing congestion in the airspace, Air Traffic Management(ATM) requires advances in massive data processing, sophisticated avionics techniques, coordination with weather updates, and assessment of multiple types of uncertainty. The complex situation overwhelms pilots and ATM controllers. To provide dependable artificial decision-making support for ATM and Unmanned Aerial System Traffic Management (UTM) systems, ontologies are an attractive knowledge technology. This paper proposes an Avionics
Analytics Ontology (AAO) to bring together different types of uncertainties including semantic from operators, sensing from navigation, and situation from weather modeling updates. The approach is aligned with the Uncertainty Representation and Reasoning Evaluation Framework (URREF), that develops an uncertainty ontology. The degree of uncertainty to improve effectiveness in ATM/UTM decision-making processes quantifies information veracity; in addition to accuracy, timeliness, and confidence. Application examples are presented that involves two ATM/UTM operation scenarios where Unmanned Aerial Vehicles (UAVs) fly nearby commercial aircraft and/or airports which requires situation awareness safety response. As compared to a baseline approach without Automatic Dependent Surveillance-Broadcast (ADS-B), results from recorded
ADS-B data demonstrate a over 0.75 veracity improvement) from Newark Liberty International Airport.


Insaurralde, C. C., & Blasch, E. (2018). Uncertainty in avionics analytics ontology for decision-making support. Journal of Advances in Information Fusion, 13(2), 255-274

Journal Article Type Article
Acceptance Date Oct 31, 2018
Publication Date Dec 31, 2018
Journal Journal of Advances in Information Fusion
Print ISSN 1557-6418
Electronic ISSN 1557-6418
Publisher International Society of Information Fusion
Peer Reviewed Peer Reviewed
Volume 13
Issue 2
Pages 255-274
Public URL
Publisher URL
Additional Information Corporate Creators : University of the West of England