Railway risk assessment - the fuzzy reasoning approach and fuzzy analytic hierarchy process approaches: A case study of shunting at Waterloo depot

Abstract

Abstract

Railway safety is a very complicated subject, which is determined by numerous aspects including human error. Many of the railway risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents a risk assessment methodology for conducting systematic risk assessment using fuzzy reasoning approach and fuzzy analytical hierarchy decision-making process. In this method, qualitative descriptors are employed to describe frequency of occurrence, consequence severity, weight factor, and risk level. The proposed risk assessment method can evaluate both qualitative and quantitative risk data, and information associated with railway operation efficiently and effectively. The outcomes of risk assessment are represented as the risk degrees and the defined risk categories of risk levels (RLs) with a belief of percentage, which provide very useful risk information to decision makers. This will provide railway risk analysts, managers, and engineers with a method and tool to improve their safety management and set safety standards. A case study of risk assessment of shunting at Waterloo depot is used to illustrate the application of the proposed methodology.