Abstract
The many varied views on resilience indicate that it is an important concept which has significance in many disciplines, from ecology to psychology to risk/disaster management. Therefore, it is important to be able to quantifiably measure the resilience of systems, and thus be able to make decisions on how the resilience of the system can be improved. In this paper we will work with the definition, due to Pimm (1991), that resilience is “how fast a variable that has been displaced from equilibrium returns to it.” We will think of a system as being more or less resilient depending on the speed with which a system recovers from disruptive events or shocks. Here we consider systems which revert to an equilibrium state from shocks, and introduce a measure of resilience by providing a quantification of the rapidity of these systems’ recovery from shocks.We use a mean-reverting stochastic model to study the diffusive effects of shocks and we apply this model to the case of the London Underground. As a shock diffuses through the network, the human-flow in the network recovers from the shock. The speed with which the passenger counts return to normal is an indicator of how quickly the line is able to recover from the shock and thereafter resume normal operations.
Highlights
The urban world is a connected network of infrastructure systems, and urban communities depend on the functioning of these infrastructures
They applied this metric to a case study of the London July 2005 subway and bus bombings, measuring static resilience in terms of transportation mode shifts applied to passenger journeys
We propose to fit our model to this data, and use the mean-reversion parameter in the model to understand the resilience of the underground line
Summary
The urban world is a connected network of infrastructure systems, and urban communities depend on the functioning of these infrastructures. Transportation systems provide one of the key infrastructure services to urban society Ensuring that these services are resilient so as to reduce the level of disruption from disasters must be an important economic and social priority. The approach is based on the comprehensive economic resilience metric proposed by Rose (2009, 2007) They applied this metric to a case study of the London July 2005 subway and bus bombings, measuring static resilience in terms of transportation mode shifts applied to passenger journeys. We propose a new quantitative measure of resilience using a mean-reverting stochastic model and we show that the model is able to capture the properties of systems with a wide variety of behaviours.
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