Abstract: The quantification of human reliability is an active and frequently controversial research area. The increasing role that the probabilistic safety assessment is playing in the regulation of aviation systems has led to the need for the development of models that produce probabilistics for human error rates, which is obvious in historical aviation accident data listed in this paper. The present paper critically reviews the recently developed models for assessing human error rates under accidental conditions. It covers the following models and methods: the human cognitive reliability model (HCR), cognitive sub-element model (CSE), nuclear regulatory commission handbook model (NRC), the technica empirica stima errori operatori (TESEO),success likelihood index methodology (SLIM) and the grey model. Suitable conditions, advantages and disadvantages of the models and methods are briefly discussed. In particular, the grey model which can deal with various man-machine environment and human reliability is considered to be the most powerful method to assess human reliability. In the meantime, this paper puts forward the new aspects that must be considered in systems reliability assignment and supervision of cockpit equipment.

Key words: human error, probabilistic risk assessment, reliability analysis