Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/13288

Title: An efficient phased mission reliability analysis for autonomous vehicles
Authors: Remenyte-Prescott, Rasa
Andrews, J.D.
Chung, Paul Wai Hing
Keywords: Phased mission
Autonomous system
Fault tree
Binary decision diagram
Issue Date: 2010
Publisher: © Elsevier
Citation: REMENYTE-PRESCOTT, R., ANDREWS, J.D. and CHUNG, P.W.H., 2010. An efficient phased mission reliability analysis for autonomous vehicles. Reliability Engineering and System Safety, 95 (3), pp. 226 - 235
Abstract: Autonomous systems are becoming more commonly used, especially in hazardous situations. Such systems are expected to make their own decisions about future actions when some capabilities degrade due to failures of their subsystems. Such decisions are made without human input, therefore they need to be well-informed in a short time when the situation is analysed and future consequences of the failure are estimated. The future planning of the mission should take account of the likelihood of mission failure. The reliability analysis for autonomous systems can be performed using the methodologies developed for phased mission analysis, where the causes of failure for each phase in the mission can be expressed by fault trees. Unmanned autonomous vehicles (UAVs) are of a particular interest in the aeronautical industry, where it is a long term ambition to operate them routinely in civil airspace. Safety is the main requirement for the UAV operation and the calculation of failure probability of each phase and the overall mission is the topic of this paper. When components or subsystems fail or environmental conditions throughout the mission change, these changes can affect the future mission. The new proposed methodology takes into account the available diagnostics data and is used to predict future capabilities of the UAV in real time. Since this methodology is based on the efficient BDD method, the quickly provided advice can be used in making decisions. When failures occur appropriate actions are required in order to preserve safety of the autonomous vehicle. The overall decision making strategy for autonomous vehicles is explained in this paper. Some limitations of the methodology are discussed and further improvements are presented based on experimental results.
Description: This article was published in the journal Reliability Engineering and System Safety [© Elsevier]. The definitive version is available at: http://dx.doi.org/10.1016/j.ress.2009.10.002
Version: Accepted for publication
DOI: 10.1016/j.ress.2009.10.002
URI: https://dspace.lboro.ac.uk/2134/13288
Publisher Link: http://dx.doi.org/10.1016/j.ress.2009.10.002
ISSN: 0951-8320
Appears in Collections:Published Articles (Computer Science)

Files associated with this item:

File Description SizeFormat
RESS 2010_UAVs.pdf296.5 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.