基于因果推断的城市地铁系统脆弱性度量方法
A Causal Inference Approach to Measure the Vulnerability of Urban Metro Systems
摘要：
公交运营商需要脆弱性措施，以了解中断情况下服务退化的程度。本文贡献了一种新的因果推断方法估计地铁系统车站级的脆弱性文献。实证分析是基于历史事件和人口层面的乘客需求的大规模数据。因此，这一分析消除了以前关于人类行为和破坏情景的研究所作假设的必要性。我们开发了四个经验脆弱性指标的基础上的因果影响中断的出行需求，平均旅行速度和客流分布。具体而言，基于客流分布不规则性的拟议指标将脆弱性测量的范围扩展到整个行程分布，而不仅仅是分析对入境或出境需求（即行程分布的时刻）的干扰影响。采用倾向得分匹配方法，对非随机发生的干扰事件所引起的混杂偏差进行调整，得到干扰影响的无偏估计。建议的框架，伦敦地铁的应用表明，地铁站的脆弱性取决于位置，拓扑结构和其他特性。我们发现，在2013年，伦敦市中心的车站更容易受到出行需求损失的影响。然而，平均旅行速度的损失和相对客流的不规则性表明，由于缺乏替代路线，来自伦敦外围车站的乘客遭受更长的个人延误。
英文摘要：
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.
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