ABSTRACT Public transit vehicles such as buses operate within shared transportation networks subject to dynamic conditions and disruptions such as traffic congestion. The operational delays caused by these conditions can propagate downstream through scheduled transit routes, affecting system performance beyond the initial delay. This paper develops an approach to measuring and assessing vehicle delay propagation in public transit systems. We fuse data on scheduled bus service with real-time vehicle location data to measure the originating, cascading and recovery locations of delay events across space with respect to time. We integrate the resulting patterns to construct stop-specific delay propagation networks. We also analyze the spatiotemporal patterns of propagating delays using parameters such as 1) transit line-based network distance, 2) total propagating delay size, and 3) distance decay. We apply our methodology using publicly available schedule and real-time location data from the Central Ohio Transit Authority (COTA) public bus system in Columbus, Ohio, USA. We find that delay initiation is spatially and temporally uneven, concentrating on specific stops in downtown and specific suburban locations. Core stops play a critical role in propagating delays to a wide range of connected stops, eventually having a disproportional impact on the on-time performance of the bus system.

中文翻译：

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使用实时数据评估公共交通性能：美国俄亥俄州哥伦布市公交运营延误的时空模式

摘要 公交车等公共交通车辆在共享交通网络中运行，受到动态条件和交通拥堵等中断的影响。由这些情况引起的运营延迟可以通过预定的运输路线向下游传播，影响超出初始延迟的系统性能。本文开发了一种测量和评估公共交通系统中车辆延迟传播的方法。我们将定期巴士服务的数据与实时车辆位置数据相融合，以测量跨空间延迟事件的起源、级联和恢复位置。我们整合产生的模式以构建特定于停止的延迟传播网络。我们还使用参数分析了传播延迟的时空模式，例如 1) 基于公交线路的网络距离，2) 总传播延迟大小，以及 3) 距离衰减。我们使用来自美国俄亥俄州哥伦布市俄亥俄州中部交通管理局 (COTA) 公共巴士系统的公开可用时刻表和实时位置数据来应用我们的方法。我们发现延迟启动在空间和时间上是不均匀的，集中在市中心和特定郊区位置的特定站点。核心停靠点在将延迟传播到范围广泛的连接停靠点方面发挥着关键作用，最终会对公交系统的准时性能产生不成比例的影响。专注于市中心和特定郊区位置的特定站点。核心停靠点在将延迟传播到范围广泛的连接停靠点方面发挥着关键作用，最终会对公交系统的准时性能产生不成比例的影响。专注于市中心和特定郊区位置的特定站点。核心停靠点在将延迟传播到范围广泛的连接停靠点方面发挥着关键作用，最终会对公交系统的准时性能产生不成比例的影响。