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Estimating the probability of failures or accidents with aerospace systems isoften necessary when new concepts or designs are introduced, as it is beingdone for Autonomous Aircraft. If the design is safe, as it is supposed to be,accident cases are hard to find. Such analysis needs some variance reductiontechnique and several algorithms exist for that, however specific modelfeatures may cause difficulties in practice, such as the case of system modelswhere independent agents have to autonomously accomplish missions within finitetime, and likely with the presence of human agents. For handling thesescenarios, this paper presents a novel estimation approach, based on thecombination of the well-established variation reduction technique ofInteracting Particles System (IPS) with the long-standing optimizationalgorithm denominated DIviding RECTangles (DIRECT). When combined, these twotechniques yield statistically significant results for extremely lowprobabilities. In addition, this novel approach allows the identification ofintermediate events and simplifies the evaluation of sensitivity of theestimated probabilities to certain system parameters.

A Method for Estimating the Probability of Extremely Rare Accidents in Complex Systems