LAUSR

Abstract Urban rail network safety is a critical sector of urban public safety. However, there is no uniform standard for the safety evaluation of the urban rail network. This paper presents a novel methodology by integrating a multilevel decision tree with a fuzzy analytical approach to enhance urban rail network safety. The proposed methodology overcomes serious limitations such as subjectivity in the data and independence of the variables in decision-making processes. The proposed methodology is applied to the risk evaluation of the selected Chongqing rail transit lines and the Expo Line. The risk analysis is considered using the field data collected from these transit lines. The applied case studies confirm the general applicability of the methodology and the multilevel decision tree network. The main risk factors identified for the Chongqing rail traffic system are the terrorist threat, emergency management, and aging infrastructure which need to be investigated as a priority to mitigate risk associated with these infrastructures.