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Due to the large number of passengers served by the metro, with its extensive served area, as well as the interconnection of different stations within the metro system, there is a high possibility that a large number of city residents' trips will be delayed or forced to be canceled and cause economic losses, once a safety accident occurs in the subway system. An easy-to-practice and highly flexible evaluation framework are proposed to explore the identification of vulnerable nodes in a weighted metro network, considering network connectivity and node traffic. The degree distribution of the passenger flow weighted network obeys the power law distribution. The relationship between node connectivity, node passenger flow, and key players in the network are also discussed. We simulated network node failures under four scenarios to assess the impact of node failures on network accessibility and the number of passengers served. The network is robust when the nodes fail randomly; the network is vulnerable to deliberate attacks based on topological node characteristics. The strategies that have the most significant impact on site traffic are node weight-based attack and node weighted-degree-based attack, with the weighted-degree-based attack being more disruptive to network connectivity and the best performing strategy in aggregate. Furthermore, we have identified the top 10 nodes in the Shenzhen Metro network that are more influential to passengers and disruptive to the network structure, which could provide a reference for metro emergency management.
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