4.5 Article

A Unified Airspace Risk Management Framework for UAS Operations

Journal

DRONES
Volume 6, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/drones6070184

Keywords

Unmanned Aircraft Systems; UAS; UAS Traffic Management; UTM; collision risk; Air Traffic Management; avionics; airspace risk; Communication; Navigation and Surveillance; CNS; Required Navigation Performance; RNP; Required Communications Performance; RCP; Required Surveillance Performance; RSP; robotics; aerial robotics; navigation; tracking; sense and avoid; detect and avoid

Categories

Funding

  1. Australian Civil Aviation Safety Authority (CASA) [19/39]

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This article proposes a comprehensive risk management framework to address the existing gaps in airspace risk assessment models by simulating UAS collision risk in all classes of airspace. The effectiveness of the proposed framework is tested in two simulation case studies.
Collision risk modelling has a long history in the aviation industry, with mature models currently utilised for the strategic planning of airspace sectors and air routes. However, the progressive introduction of Unmanned Aircraft Systems (UAS) and other forms of air mobility poses new challenges, compounded by a growing need to address both offline and online operational requirements. To address the associated gaps in the existing airspace risk assessment models, this article proposes a comprehensive risk management framework, which relies on a novel methodology to model UAS collision risk in all classes of airspace. This methodology inherently accounts for the performance of Communication, Navigation and Surveillance (CNS) systems, and, as such, it can be applied to both strategic and tactical operational timeframes. Additionally, the proposed approach can be applied inversely to determine CNS performance requirements given a target value of collision probability. This new risk assessment methodology is based on a rigorous analysis of the CNS error characteristics and transformation of the associated models into the spatial domain to generate a protection volume around each predicted air traffic conflict. Additionally, a methodology to quickly and conservatively evaluate the multi-integral formulation of collision probability is introduced. The validity of the proposed framework is tested using representative CNS performance parameters in two simulation case studies targeting, respectively, a terminal manoeuvring area and an enroute scenario.

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