Quantitative Analysis of Human Error Probability in High-Speed Railway Dispatching Tasks

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.

Keywords

• Cognitive reliability and error analysis method (CREAM)
• human error probability (HEP)
• common performance condition (CPC)
• high-speed railway dispatchers
• 2-tuple linguistic term sets
• evidential reasoning (ER)