Resilience of Metrorail Networks: Quantification With Washington, DC as a Case Study

Abstract

Abstract According to the United Nation's Department of Economic and Social Affairs Population Division, 66% of the world's population will reside in urban areas by 2050, a boost from 30% in 1950. Urbanization has indeed triumphed and has increased the demand for infrastructure systems including metrorail networks, one of the most tangible examples of complex transportation infrastructure systems. A synergistic rapid growth of urban population concurrent with great increases in metrorail use may lead to perturbations in the state of such a system. Taking into consideration of such perturbations and developing appropriate resilience measurements are paramount to the design of sustainable, robust, and resilient systems capable of performing satisfactorily through intentional and/or stochastic disruptions. As such, developing resilience metrics in a structured and appropriate manner is necessary. Using Washington, DC Metro as a case study, this paper examines metrorail network resilience and associated metrics with well-defined relationships to vulnerability and tied to efficiency. This examination includes developing a metro rail model in a graph form and obtaining its basic features by network topology analysis. The analytical work demonstrates that the Washington, DC Metro with its 91 stations and 140 links is a small-world network with the presence of a scale-free phenomenon and of a high level of vulnerability in the case of disruptive events. Evaluation of the efficiency and vulnerability of a metrorail network after disruption requires the consideration of two primary failure events, i.e., the failure of a metro station and the failure of a metro segment between stations. Vulnerability evaluation identifies the most critical stations and rail segments as illustrated using the Washington, DC Metro network. Such an assessment offers a logical basis to enhance system resilience and develop postfailure recovery strategies.