Abstract
Human error can be regarded as a significant factor contributing to high-speed railway accidents. Cognitive Reliability and Error Analysis Method (CREAM) is well-known approach applied to determine Human Error Probability (HEP). However, shortcomings are still disclosed and weaken the applicability of such approach. These include the lack of sufficient failure data, lack of valid description of Common Performance Condition (CPC) and does not consider the CPCs weights. In addition, Basic CREAM does not provide a method to calculate the concrete HEP. In this paper, a modified CREAM is proposed to assess HEP of high-speed railway dispatchers in dispatching tasks. The core of the modified method is to use 2-tuple linguistic term sets to describe CPCs evaluation, combine weighted CPCs by Evidential Reasoning (ER) approach, and adopt Multi-Attribute Group Decision-Making (MAGDM) method to calculate HEP. To make CPCs weights more accurate, dynamically adjusting weights is adopted in this paper. The rationality and validity of the modified CREAM approach are verified by two axioms and compared other models. Finally this modified CREAM approach is applied to human reliability analysis of high-speed railway dispatchers.
Highlights
In recent years, high-speed railway has developed rapidly in China
In order to make the calculation of weights more accurate, we provide a combined model to determine the Common Performance Condition (CPC) weights in this paper
Since the initial D (r) is 0.002614, the abscissa δ starts at 0.0025. As it can be seen from Figure.6, the human error probability (HEP) influenced by changing the different δ values, but when δ < 0.0001, the impact on HEP becomes less significant. This is because when experts do not reach a certain consensus, it has a great impact on the attributes (i.e. CPCs) and experts’ weights, which in turn affects the calculation of HEP
Summary
High-speed railway has developed rapidly in China. By the end of 2019, the operating mileage of high-speed railway in China has exceeded 35000 kilometers, accounting for about 70% of the world’s total. Y. Sun et al.: Quantitative Analysis of HEP in High-Speed Railway Dispatching Tasks methodologies of HRA focus on the study of human behavior theory and error classification, and forms a statistical analysis and prediction method of human error probability (HEP) based on operator experience and expert judgment, among which Technique for Human Error Rate Prediction (THERP) is the representative method [7]. The above methods have made remarkable achievements in the field of HRA, if CREAM is used to determine the HEP of high-speed railway dispatchers, there are still some problems need to be solved in the existing research on the CREAM method:(1) Lack of reliable historical data. The main contributions of this work are shown in the following: (1) Constructed the CPCs detailed evaluation rules for high-speed railway dispatchers, and used 2-tuple linguistic term sets to evaluate CPCs to characterize the fuzziness and uncertainty of information. Definition 4 [17]: Let (si, αi) and (sj, αj) be two 2-tuples, the distance between (si, αi) and (sj, αj) is defined as follows:
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