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Semantic Scholar · Article (Symposium on Dependable Autonomic and Secure Computing)
A Unified Collision Risk Model for Unmanned Aircraft Systems
Attribution
This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Symposium on Dependable Autonomic and Secure Computing.
Abstract
Verbatim from Semantic Scholar. Not paraphrased, not summarized.
This paper proposes a novel risk management framework, and specifically a methodology to model UAS collision risk. The model inherently accounts for the performance of Communication, Navigation and Surveillance (CNS) systems, as well as aircraft vehicle dynamics in evaluating collision risk. The model is applicable to encounters between two or more aircraft, and to terrain collision scenarios. The methodology is underpinned by modelling of the CNS error characteristics, as well as wind uncertainty, and the translation of those characteristics to the spatial domain to form a virtual risk protection volume around each aircraft. The volume is then inflated in proportion to a Target Level of Safety (TLS). The methodology is demonstrated in a simulation case study representative of aircraft-aircraft collision encounters. A 2σ navigation accuracy bound of 185.2 m was found to incur a maximum collision risk of approximately 1.5×10-4 at a separation of 200m.
Authors
- Suraj Bijjahalli
- A. Gardi
- Nichakorn Pongsakornsathien
- R. Sabatini
Keywords
- Engineering
- Computer Science
Citation: Suraj Bijjahalli, A. Gardi, Nichakorn Pongsakornsathien , et al. (2021). A Unified Collision Risk Model for Unmanned Aircraft Systems. Symposium on Dependable Autonomic and Secure Computing. Semantic Scholar ID 5fab156de1dc3c9687484edd48bd4bc83292b78b. https://doi.org/10.1109/dasc52595.2021.9594342 ↗