Risk Assessment Model for Urban Rail Transit System Based on Bayesian Network-ISM

Urban rail transit has become one of the main modes of people's travel. Once an accident happens in the urban rail system, it will reduce the traffic efficiency and affect people's normal life. Therefore, it is very necessary to evaluate the safety risks faced by the system during its operation and put forward effective safety management measures. In this paper, a safety risk assessment method combining PCA-ISM- Bayesian network is proposed. Firstly, 61 risk indexes are extracted from the collected Beijing subway accident data by combining with “subway operation safety evaluation standard”, and the index system is constructed by PCA method. Secondly, use the ISM model to analyze the logical relationship and build a hierarchical structure among indexes. Finally, the Bayesian network is embedded to build a security risk evaluation model to evaluate the internal risk of the system. The result shows that the safety degree of Beijing subway is acceptable.