Managing uncertainty in the system safety assessment of unmanned aircraft systems

There is much debate over the development of suitable system safety requirements for Unmanned Aircraft Systems (UAS). A particular point of contention is the approach for determining the allowable average probability per flight hour of failure conditions. For UAS, there is limited knowledge and data to inform the assessment of the average probability of failure conditions. This leads to uncertainty in the system safety assessment (SSA) process. Current literature provides no discussion as to how this uncertainty can be managed in the system safety certification (SSC) of a UAS. In addition to this, uncertainty in the average probability of failure conditions is not accounted for in compliance findings, which can result in subjective certification decision-making. This research proposes a new framework for system safety certification under conditions of uncertainty. The new framework is briefly introduced, with the focus of this paper being on the characterisation of uncertainty within the SSA process. A Bayesian approach to the modelling of the average probability of failure conditions is adopted. The traditional assumption of a constant failure rate model is challenged; with a Weibull distribution proposed as a more appropriate representation of UAS failure occurrence.