Subway System Safety Risk Analysis Based on Bayesian Network

摘要

Subway system is associated with a high level of uncertainty because it usually operates in a dynamic environment in which technical and human and organizational malfunctions may cause possible accidents. This paper proposes a Bayesian network approach to model causal relationships among risk factors. This model explicitly represents cause and effect assumptions between variables. The method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinions when quantitative data are lacking. This makes the risk and safety analysis of subway systems more functional and easier. A case study of the fire risk due to human errors during operation is used to illustrate the application of the proposed model.