Ontological knowledge representation for avionics decision-making support

Abstract

Air Traffic Management (ATM) incorporates demanding decision-making processes that combine information of diverse characteristics. ATM challenges aviators and airspace controllers with unprecedented workloads to maintain safety and cross-checking of multi-source information, including data from Unmanned Aerial Vehicles (UAVs). The challenge for future ATM Decision-Support Systems (DSS) is not only autonomous and reliable complex decision-making with minimal human intervention but also dealing with UAV ATM (UTM). This paper proposes the implementation of Ontologies for NextGen Avionics Systems (ONAS) for UTM. ONAS presents an operation framework and an ontology-based tool to support decision making in advanced ATM/UTM systems. The proposed ONAS approach includes a cognitive ATM/UTM architecture for avionics analytics. An ontological database captures information related to weather, flights, and airspace. Inference over the ontology is provided by a reasoner. The decision-making process is underpinned by the concept of Situation AWareness (SAW) as well as Situation Assessment (SA). The SAW approach proposed is intended to be initially used in civil aviation. A case study is presented based on different scenarios for an ATM/UTM system. The scenarios represent flight situations where the decisions made are supported by the proposed ONAS approach.