Resilience-Based Strategies for Topology Enhancement and Recovery of Metrorail Transit Networks

Abstract

Metro networks are complex systems that provide efficient and reliable transportation services for communities and play prominent roles in sustaining local economies, yet investments and safety enhancements to the networks may not receive appropriate attention. Metro networks consist of a large number of interacting nodes and links. Any adverse event leading to disrupted network components’ interaction and connectivity would dramatically affect the safety and well-being of commuters as well as direct and indirect costs associated with performance loss. Therefore, enhancing network resilience could lead to a boost in network efficiency and performance, ideally taken in a cost-effective manner. This paper provides a methodology to quantitatively measure the most vulnerable segments of a metro network using the Washington, DC Metro as a case study. Analyzing the network vulnerability is a basis to measure the resilience of the network. This paper then offers strategies to increase the resilience of the metro by enhancing its topology prior to any failure, such as adding an interloop (loop line hereafter) to the network. In addition, an approach to identifying proper postfailure recovery strategies with special attention not only on restoring connectedness but also on minimizing the total cost associated with a disruptive event resulting in resilience loss is extensively elucidated. The analysis results show that the most vulnerable segments of the Washington, DC Metro are transfer stations and their associated links located in the central part of the city. As such, adding an optimal loop line could create redundancy to these vulnerable segments and improve network resilience by increasing the network efficiency. Furthermore, the proposed recovery analysis and cost model herein enables decision-makers to identify the best recovery strategy according to both paramount recovery sequence and minimum cost consideration. The best recovery sequence typically reflects the order of components ranked based on their degree of vulnerability in the network. The use of the methodology proposed herein may lead to significant societal benefits by reducing the risk of catastrophic failures, providing references for mitigation of disruption due to adverse events, justifying capital improvements to the network, and related pursuits.