Modeling network resilience of rail transit under operational incidents

In the context of urban rail network analysis, most studies have focused on vulnerability analysis developing methodologies to measure consequences on network performance under destroy events. Few works are reported addressing the modeling of rail transit network resilience under operational incidents which could be more important analyzing the network performance changes under daily operations. This study demonstrates a resilience approach for rail transit network under daily operational incidents. Integrating the network topological and passenger volume characteristics, this approach explicitly accounts for the impacts of accumulative affected passengers quantifying the varying resilience of rail network with time under different incidents. The proposed methodology was applied to Shanghai Metro Network in Shanghai, China. Results show that critical stations are identified differently depending on duration time of different incidents and characteristics of the failed stations, and stations on network legs could be more important than those with redundant rail alternatives. Conclusions of this research would also have practical implications for the management and decision making of rail transit network under daily operational incidents.