Citation

Xu H, Zhang Y, Li H, Skitmore M, Yang J, Yu F. J. Rail. Transp. Plan. Manag. 2019; 11: e100148.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.jrtpm.2019.100148

PMID

unavailable

Abstract

Rail systems in urban areas have been developing rapidly in recent years. Numerous risk events at rail stations reveal the vulnerability of rail system. The interdependent risks in the stations interact with each other and may further form risk interaction chains and networks. However, most of the studies treat risks independently. In response, this paper aims to explore the safety risk interactions in rail stations as they can be as serious as those in rail systems generally. This involves a four-step case study. In step I, 62 rail station risk events were collected from 62 stations worldwide. 25 risks are then identified from these events and 241 risk interaction chains extracted in steps II and III respectively. In the last step, the 241 chains are used to construct a Bayesian network to identify their sensitivity levels and the key risk chains. This shows there are 8 sensitive risks and 9 key risk interaction chains. This paper proposes a risk interaction analysis method for the operational risks in the rail station. The results provide a better understanding of rail station safety and are beneficial for formulating the safety management strategies of rail stations worldwide.

Language: en

Keywords

Influence strength; Rail station; Risk interaction chain; Risk interaction network; Sensitivity analysis