PDF(Pubmed)
Abstract：
COVID-19 has swept the world, and the unprecedented decline in transit ridership has been noticed. However, little attention has been paid to the resilience of the transportation system, particularly in medium-sized cities. Drawing upon a light rail ridership dataset in Salt Lake County from 2017 to 2021, we develop a novel method to measure the vulnerability and resilience of transit ridership using a Bayesian structure time series model. The results show that government policies have a more significant impact than the number of COVID-19 cases on transit ridership. Regarding the built environment, a highly compact urban design might reduce the building coverage ratio and makes transit stations more vulnerable and less resilient. Furthermore, the high rate of minorities is the primary reason for the drops in transit ridership. The findings are valuable for understanding the vulnerability and resilience of transit ridership to pandemics for better coping strategies in the future.
摘要：
COVID-19席卷全球,人们注意到过境乘客量的空前下降。然而,很少关注交通系统的弹性，特别是在中等城市。利用2017年至2021年盐湖县的轻轨乘客数据集，我们开发了一种新颖的方法，使用贝叶斯结构时间序列模型来测量公交乘客的脆弱性和弹性。结果表明，与COVID-19病例数相比，政府政策对过境乘客人数的影响更大。关于建筑环境，高度紧凑的城市设计可能会降低建筑物的覆盖率，并使公交车站更加脆弱和弹性降低。此外，少数民族的高比率是过境乘客减少的主要原因。这些发现对于了解过境乘客对流行病的脆弱性和复原力，以便在未来采取更好的应对策略是有价值的。
