Abstract
With increasing passenger flows and construction scale, metro systems in metropolises have entered a new era of networking operation and become the most effective way to alleviate and decrease traffic congestion. However, frequent occurrence of random failures and malicious attacks pose a serious threat to metro security and reliability. Thus, it is necessary to quantitatively evaluate the vulnerability of the metro network to different failures or attacks from a networking perspective. Based on the complex network theory, this study took the Shanghai Metro Network (SMN) as an example to investigate vulnerability of a weighted metro network in responding to random failures as well as malicious attacks. In particular, compared to topological networks, the vulnerability of weighted networks was analyzed to investigate how traffic and spatial constraints influence the transport system’s vulnerability, since topological features of complex networks are often associated with the weights of the edges and spatial constraints. Simulation results show that the SMN is robust against random failures but fragile for malicious attacks. The vulnerability analysis of weighted properties shows that all targeted attacks are capable to shatter the network’s communication or transport properties at a very low level of removed nodes and the highest betweenness attack strategy is the most effective mode to cause destructive effects on SMN among five attack or failure strategies. The inclusion of passenger flows provides evidence for the view that topological networks cannot convey all the information of a real-world network and traffic flow in the network should be considered as one of the key features in the finding and development of defensive strategies. Our results provide a richer view on complex weighted networks in real-world and possibilities of risk analysis and policy decisions for the metro operation department.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have