Ontology-Based Situation Awareness for Air and Space Traffic Management

Carlos C. Insaurralde, Erik Blasch, Roberto Sabatini

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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).

Original languageBritish English
Title of host publication2022 IEEE/AIAA 41st Digital Avionics Systems Conference, DASC 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665486071
DOIs
StatePublished - 2022
Event41st IEEE/AIAA Digital Avionics Systems Conference, DASC 2022 - Portsmouth, United States
Duration: 18 Sep 202222 Sep 2022

Publication series

NameAIAA/IEEE Digital Avionics Systems Conference - Proceedings
Volume2022-September
ISSN (Print)2155-7195
ISSN (Electronic)2155-7209

Conference

Conference41st IEEE/AIAA Digital Avionics Systems Conference, DASC 2022
Country/TerritoryUnited States
CityPortsmouth
Period18/09/2222/09/22

Keywords

  • Artificial Cognition
  • Avionics Analytics
  • Decision-Making Support
  • Ontologies

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