Research on Risk Consequence Severity Evaluation Based on Fuzzy Analytic Hierarchy Process and Evidence Theory

Abstract

In view of the uncertainty of the severity of the consequences of the Chinese train control system level 2 (CTCS-2) risk events, the paper puts forward a combined approach to evaluate the consequence severity of a risk event by using the fuzzy analytic hierarchy process and the discount evidence theory on the basis of expert scoring. Firstly, the evaluation index system of consequence severity is established, and the weights of the evaluation indices are calculated by using the fuzzy analytic hierarchy process. Secondly, the membership degree of each evaluation index’s severity grade is calculated by using discount evidence theory. Finally, the weights are multiplied with the membership degree, and the severity grade of risk consequence is determined according to the maximum membership principle. In this paper, taking the CTCS-2 train control system ‘train overspeed unprotected’ risk event as an example, based on expert scoring, the consequence severity of the risk event is evaluated by using fuzzy analytic hierarchy process (FAHP) and discounted evidence theory, and the consequence severity of the risk event is assessed as ‘very serious,’ which is consistent with our common sense.