A Bayesian approach to system safety assessment and compliance assessment for Unmanned Aircraft Systems

Washington, A, Clothier, R and Williams, B 2017, 'A Bayesian approach to system safety assessment and compliance assessment for Unmanned Aircraft Systems', Journal of Air Transport Management, vol. 62, pp. 18-33.


Document type: Journal Article
Collection: Journal Articles

Title A Bayesian approach to system safety assessment and compliance assessment for Unmanned Aircraft Systems
Author(s) Washington, A
Clothier, R
Williams, B
Year 2017
Journal name Journal of Air Transport Management
Volume number 62
Start page 18
End page 33
Total pages 16
Publisher Elsevier
Abstract This paper presents a new approach to showing compliance to system safety requirements for aviation systems. The aim is to improve the objectivity, transparency, and rationality of compliance findings in those cases where there is uncertainty in the assessments of the system. A Bayesian approach is adopted that facilitates a more comprehensive treatment of the uncertainties inherent to all system safety assessments. The assessment and compliance framework is reformulated as a problem of decision making under uncertainty, and a normative decision approach is used to illustrate the approach. A case study system safety assessment of a civil unmanned aircraft system is used to exemplify the proposed approach. The proposed approach could be readily applied to any regulatory compliance process and would represent a significant change to, and advancement over, current aviation safety regulatory practice. This paper is the first to describe the application of Bayesian techniques to the field of aviation system safety analysis. The adoption of the proposed compliance approach would bring aviation system safety practitioners in line with more contemporary (and well established) approaches adopted in the nuclear power and space launch industries.
Subject Aerospace Engineering not elsewhere classified
Keyword(s) Unmanned aircraft systems
System safety
Bayesian
Uncertainty
Regulation
Part 1309
DOI - identifier 10.1016/j.jairtraman.2017.02.003
Copyright notice © 2017 Elsevier Ltd
ISSN 0969-6997
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
Altmetric details:
Access Statistics: 190 Abstract Views  -  Detailed Statistics
Created: Wed, 29 Mar 2017, 10:24:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us