TY - JOUR
T1 - A Unified Airspace Risk Management Framework for UAS Operations
AU - Bijjahalli, Suraj
AU - Gardi, Alessandro
AU - Pongsakornsathien, Nichakorn
AU - Sabatini, Roberto
AU - Kistan, Trevor
N1 - Funding Information:
Portions of this research were supported by the Australian Civil Aviation Safety Authority (CASA) under contract no. 19/39—Airspace Risk Modelling Research Program (ARM-RP).
Publisher Copyright:
© 2022 by the authors.
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - aerial robotics
KW - Air Traffic Management
KW - airspace risk
KW - avionics
KW - CNS
KW - collision risk
KW - Communication, Navigation and Surveillance
KW - detect and avoid
KW - navigation
KW - RCP
KW - Required Communications Performance
KW - Required Navigation Performance
KW - Required Surveillance Performance
KW - RNP
KW - robotics
KW - RSP
KW - sense and avoid
KW - tracking
KW - UAS
KW - UAS Traffic Management
KW - Unmanned Aircraft Systems
KW - UTM
UR - http://www.scopus.com/inward/record.url?scp=85136215343&partnerID=8YFLogxK
U2 - 10.3390/drones6070184
DO - 10.3390/drones6070184
M3 - Article
AN - SCOPUS:85136215343
SN - 2504-446X
VL - 6
JO - Drones
JF - Drones
IS - 7
M1 - 184
ER -