Ontology-based situation awareness for air and space traffic management

Insaurralde, Carlos C.; Blasch, Erik; Sabatini, Roberto

Abstract

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).

Citation

Insaurralde, C. C., Blasch, E., & Sabatini, R. (2022). Ontology-based situation awareness for air and space traffic management. In 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC). https://doi.org/10.1109/DASC55683.2022.9925810

• Conference Name: 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC)
• Conference Location: Portsmouth, VA, USA
• Start Date: Sep 18, 2022
• End Date: Sep 22, 2022
• Acceptance Date: Apr 13, 2022
• Publication Date: Oct 31, 2022
• Deposit Date: Feb 7, 2023
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Series ISSN: 2155-7209
• Book Title: 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC)
• DOI: https://doi.org/10.1109/DASC55683.2022.9925810
• Keywords: Decision-Making Support, Artificial Cognition, Ontologies, Avionics Analytics, Space vehicles, Automation, OWL, Aerospace electronics, Ontologies, Cyber-physical systems, Air traffic control
• Public URL: https://uwe-repository.worktribe.com/output/10148488
• Publisher URL: https://ieeexplore.ieee.org/document/9925810
• Related Public URLs: https://ieeexplore.ieee.org/xpl/conhome/9925245/proceeding