2025 Agenda

As airspace systems evolve to accommodate drones, advanced air mobility and increasingly diverse aviation activity, traditional approaches to airspace safety and access are reaching their limits. Regulatory and operational decisions are often still based on qualitative judgement and static classifications, limiting the ability to assess risk consistently, transparently and at scale.

This joint presentation by the Queensland University of Technology (QUT), its project partners (Boeing and FlyFreely), and Aireon presents a data-driven framework that enables airspace collision risk to be assessed in a consistent, repeatable and operationally meaningful way across national airspace systems. Developed through the government-funded Australian Digital Airspace Characterisation (ADAC) project and based on more than four years of development, the approach represents a shift from descriptive airspace categorisation to quantified, spatially resolved risk assessment.

At the core of the framework are data-driven and data-informed probabilistic collision risk models for regions with good and limited surveillance coverage, respectively. Collision risk is quantified at fine spatial and temporal scales using a combination of established and novel aviation risk modelling techniques, innovative data management approaches, and high-performance computing. Risk metrics are visualised using standard geographic information systems and custom online applications, in a manner that is interpretable and customisable for regulatory, operational and policy decision-making. Crucially, this approach provides a bridge between quantitative analysis and qualitative judgement, supporting defensible, evidence-based and unbiased risk categorisation across most airspace environments.

The presentation will highlight the unique and distinguishing features of these models compared to existing approaches, before focusing on national-scale results and real-world case study applications with additional partners. It will demonstrate how robust, quantitative, high-resolution risk models can support a wide range of applications for uncrewed aviation (for example, risk-based assessments and approvals), crewed aviation (such as airspace change assessment, safety intervention prioritisation and evaluation of emerging operational concepts), as well as policy and regulatory development.

This collaboration illustrates how research capability and operational surveillance infrastructure can be combined to move from analysis to implementation at high technology readiness levels. While demonstrated in an Australian context, the underlying framework is jurisdiction-agnostic and can be adapted to other national and regional airspace systems by adjusting data inputs, thresholds and governance settings.