Abstract

Erroneous human behavior is often cited as a major factor to system failure. However, the complexity of the human-automation interaction can make it difficult for engineers to anticipate how erroneous human behavior can contribute to failures. In this work, we introduce a novel method for generating human errors based on the task-based taxonomy of erroneous human behavior. This allows erroneous acts to manifest as divergences from task models. We implement our method using the Enhanced Operator Function Model. We further show how the method can be used with formal system modeling and formal verification with model checking to prove whether or not potentially unanticipated erroneous behavior could contribute to system failures. We evaluate how our method scales and use it to evaluate three case studies: a radiation therapy machine, a pain medication pump, and an Apache helicopter. We discuss these results and explore options for future work.

Full Text
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