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Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London

机译:了解公共交通中断对共享自行车出行方式的影响:以伦敦地铁罢工为例

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The interdependencies between bicycle sharing and public transportation systems are not yet fully understood. This paper aims to measure and characterize the impacts of a public transportation disruption on bicycle sharing mobility patterns in London using data from more than 1 million bicycle trips from July 2015. The paper provides a comparative analysis of bicycle sharing spatial mobility patterns before, during, and after a disruption in public transportation system. We also apply a complex network-theoretic approach to uncover the impact of the disruption on the connectivity of the bicycle sharing usage network. We found that the disruption in public transportation in London increased the total number of bicycle sharing trips by 85% from an average 38,886 to 72,503 trips per day. The duration of trips also increased by 88% from an average 23 to 43 min. The disruption also had a considerable impact on the structure and properties of the bicycle sharing mobility network. The connectivity of the network of bicycle sharing trips increased by 88% from 0.102 to 0.187. We found that many of the observed changes are heterogeneously distributed over space suggesting that the impact of the disruption was not uniform across the network. However, the structure of communities in the bicycle sharing mobility network remained roughly invariant from day to day. The applied geo-statistical approach complemented with the complex network-driven methodology provides a better understanding of the interdependencies between the bicycle sharing and public transportation systems in London.
机译:自行车共享和公共交通系统之间的相互依存性尚未完全了解。本文旨在使用2015年7月以来超过1百万次自行车出行的数据来衡量和表征公共交通中断对伦敦自行车共享出行方式的影响。本文对自行车共享空间出行方式进行了比较分析,以及公共交通系统中断之后。我们还应用了复杂的网络理论方法来揭示中断对自行车共享使用网络的连接性的影响。我们发现,伦敦公共交通的中断使单车共享出行总数从平均每天38,886次增加到每天72,503次,增加了85%。出行时间从平均23分钟到43分钟也增加了88%。破坏也对自行车共享出行网络的结构和性能产生了很大影响。共享单车旅行网络的连通性从0.102增加到0.187,增长了88%。我们发现,许多观察到的变化在空间上是异构分布的,这表明破坏的影响在整个网络中并不均匀。然而,自行车共享出行网络中的社区结构每天仍然大致不变。应用的地统计方法与复杂的网络驱动方法相辅相成,可以更好地了解伦敦的自行车共享与公共交通系统之间的相互依赖性。

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