Human Reliability Assessment of Space Teleoperation Based on ISM-BN

Abstract

Space teleoperation systems, as complex giant systems, feature performance-influencing factors that are interrelated. Accurately describing the dependence between these factors is crucial for constructing a human factor reliability assessment (HRA) model. Moreover, data scarcity has consistently been a challenge in space HRA. There are primarily two types of data in this domain: expert judgment data and empirical data (simulation data, actual reports), each with complementary effects. The expert judgment data, although subjective, are readily accessible, while empirical data provide robust objectivity but are difficult to obtain. Addressing these challenges, this paper constructs an HRA model for space teleoperation that combines Interpretive Structural Modeling (ISM) with a two-stage Bayesian update method. This model reflects the dependencies between factors and accommodates multisource data (expert judgment and experimental data). With more empirical data, the model can be continuously updated and refined to yield increasingly accurate evaluations of human error probability (HEP). The validity of the model was verified through the analysis of 52 space incidents using the N-K model. The study provides a methodological foundation for HRA in other space missions.