Discovering the Hidden Community Structure of Public Transportation Networks
Discovering the Hidden Community Structure of Public Transportation Networks
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DOI：
10.1007/s11067-019-09476-3
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发表时间：
2020-03-01
影响因子：
2.4
通讯作者：
Gardner, Lauren M.
中科院分区：
文献类型：
--
作者：
Hajdu, Laszlo;Bota, Andras;Gardner, Lauren M.
公共交通建模和智能卡技术的进步可以揭示乘客的详细接触模式。表示这种联系模式的自然方式是以网络的形式。本文利用大城市公共交通分配模型中已知的联系模式，提出了两种新型网络结构的发展，每一种网络结构都阐明了乘客出行行为的某些方面。我们首先提出了一个换乘网络的发展，它可以揭示在给定的一天一起旅行的乘客群体。其次，我们提出了一个社区网络的发展，该网络源于换乘网络，并捕捉乘客之间的旅行模式的相似性。然后，我们探索了这些网络结构的应用，以确定公共交通系统中最常用的旅行路径，即路线和换乘，并分别在公共交通网络的乘客中建立流行病传播风险模型。在后一种情况下，我们的结论强化了之前的观察结果，即在疫情爆发期间，上午和下午高峰时段穿越或连接市中心的路线是最“危险”的。
Advances in public transit modeling and smart card technologies can reveal detailed contact patterns of passengers. A natural way to represent such contact patterns is in the form of networks. In this paper we utilize known contact patterns from a public transit assignment model in a major metropolitan city, and propose the development of two novel network structures, each of which elucidate certain aspects of passenger travel behavior. We first propose the development of a transfer network, which can reveal passenger groups that travel together on a given day. Second, we propose the development of a community network, which is derived from the transfer network, and captures the similarity of travel patterns among passengers. We then explore the application of each of these network structures to identify the most frequently used travel paths, i.e., routes and transfers, in the public transit system, and model epidemic spreading risk among passengers of a public transit network, respectively. In the latter our conclusions reinforce previous observations, that routes crossing or connecting to the city center in the morning and afternoon peak hours are the most "dangerous" during an outbreak.