TY - GEN
T1 - Ontology-Based Situation Awareness for Air and Space Traffic Management
AU - Insaurralde, Carlos C.
AU - Blasch, Erik
AU - Sabatini, Roberto
N1 - Funding Information:
This material is based upon work supported by the European Aerospace Office of Research and Development. The use of ontologies in aviation proliferates and supports the evolution of many avionics’ technologies. For example, the FAA and Eurocontrol continually push for ontologies as a key tool for the development of future ATM systems. Additionally, the Avionics Analytics Ontology (AAO) [8] has been developed as a cognitive engine of a Decision Support System (DSS) for avionics and ATM applications.
Funding Information:
This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-19-1-7038.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The rapid technological and business advances of point-to-point space transport prompt the need for an integrated Air Traffic Management (ATM) and Space Traffic Management (STM) framework. The introduction of a more flexible airspace and vehicle/trajectory management services aims to harmonize the requirements of multi-domain and multi-entity stakeholders. The ATM-STM integration problem involves related air-and-space transport issues such as separation assurance/collision avoidance,, airspace capacity management, atmospheric pollution and emissions, and cybersecurity. To meet the ATM-STM integration challenges, ontologies are an attractive approach to enact and enhance situational awareness in such an integrated ATM-STM domain. In fact, the Federal Administration Agency (FAA) NextGen (Next Generation Air Transport Management) and SESAR (Single European Sky ATM Research) programs, as well as NASA, have proposed the use of ontologies to represent knowledge in the rapidly evolving ATM context. This paper presents a discussion on considerations to develop an Ontological Situation Awareness (OSAW) approach, which could be applied to an integrated air-and-space operational domain. These considerations include (1) both operational/technical challenges and opportunities, (2) the adoption of Artificial Intelligence (AI) and the associated impacts Cyber-Physical Systems (CPS) certifiability, and (3) contributions to sustainability using the OSAW. Realistic scenarios are presented to demonstrate the possible uses of the OSAW approach and how a Space Avionics Analytics Ontology (SAAO) can contribute to the development of an OSAW system for multi-domain traffic management. The SAAO also considers aircraft and spacecraft which are manned/unmanned with various degrees of automation (categories defined in line with current aviation/aerospace industry standards) and trusted autonomy (as an attribute of the applicable automation categories).
AB - The rapid technological and business advances of point-to-point space transport prompt the need for an integrated Air Traffic Management (ATM) and Space Traffic Management (STM) framework. The introduction of a more flexible airspace and vehicle/trajectory management services aims to harmonize the requirements of multi-domain and multi-entity stakeholders. The ATM-STM integration problem involves related air-and-space transport issues such as separation assurance/collision avoidance,, airspace capacity management, atmospheric pollution and emissions, and cybersecurity. To meet the ATM-STM integration challenges, ontologies are an attractive approach to enact and enhance situational awareness in such an integrated ATM-STM domain. In fact, the Federal Administration Agency (FAA) NextGen (Next Generation Air Transport Management) and SESAR (Single European Sky ATM Research) programs, as well as NASA, have proposed the use of ontologies to represent knowledge in the rapidly evolving ATM context. This paper presents a discussion on considerations to develop an Ontological Situation Awareness (OSAW) approach, which could be applied to an integrated air-and-space operational domain. These considerations include (1) both operational/technical challenges and opportunities, (2) the adoption of Artificial Intelligence (AI) and the associated impacts Cyber-Physical Systems (CPS) certifiability, and (3) contributions to sustainability using the OSAW. Realistic scenarios are presented to demonstrate the possible uses of the OSAW approach and how a Space Avionics Analytics Ontology (SAAO) can contribute to the development of an OSAW system for multi-domain traffic management. The SAAO also considers aircraft and spacecraft which are manned/unmanned with various degrees of automation (categories defined in line with current aviation/aerospace industry standards) and trusted autonomy (as an attribute of the applicable automation categories).
KW - Artificial Cognition
KW - Avionics Analytics
KW - Decision-Making Support
KW - Ontologies
UR - http://www.scopus.com/inward/record.url?scp=85141937551&partnerID=8YFLogxK
U2 - 10.1109/DASC55683.2022.9925810
DO - 10.1109/DASC55683.2022.9925810
M3 - Conference contribution
AN - SCOPUS:85141937551
T3 - AIAA/IEEE Digital Avionics Systems Conference - Proceedings
BT - 2022 IEEE/AIAA 41st Digital Avionics Systems Conference, DASC 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st IEEE/AIAA Digital Avionics Systems Conference, DASC 2022
Y2 - 18 September 2022 through 22 September 2022
ER -
