A causal inference approach to measure the vulnerability of urban metro systems
Document Type
Journal Article
Publication Date
2021
Subject Area
place - urban, place - europe, mode - subway/metro, ridership - demand, planning - methods, planning - service level, land use - impacts
Keywords
Vulnerability, Urban metro system, Causal inference, Propensity score matching
Abstract
Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need for assumptions made by previous studies on human behaviour and disruption scenarios. We develop four empirical vulnerability metrics based on the causal impact of disruptions on travel demand, average travel speed and passenger flow distribution. Specifically, the proposed metrics based on the irregularity in passenger flow distribution extends the scope of vulnerability measurement to the entire trip distribution, instead of just analysing the disruption impact on the entry or exit demand (that is, moments of the trip distribution). The unbiased estimates of disruption impact are obtained by adopting a propensity score matching method, which adjusts for the confounding biases caused by non-random occurrence of disruptions. An application of the proposed framework to the London Underground indicates that the vulnerability of a metro station depends on the location, topology, and other characteristics. We find that, in 2013, central London stations are more vulnerable in terms of travel demand loss. However, the loss of average travel speed and irregularity in relative passenger flows reveal that passengers from outer London stations suffer from longer individual delays due to lack of alternative routes.
Rights
Permission to publish the abstract has been given by SpringerLink, copyright remains with them.
Recommended Citation
Zhang, N., Graham, D.J., Hörcher, D. & Bansal, P. (2021). A causal inference approach to measure the vulnerability of urban metro systems. Transportation, Vol. 48, pp. 3269–3300.
