Scaling in the recovery of urban transportation systems from massive events
Scaling in the recovery of urban transportation systems from massive events
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DOI：
10.1038/s41598-020-59576-1
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发表时间：
2020-02-17
影响因子：
4.6
通讯作者：
Ramasco, Jose J.
中科院分区：
文献类型：
--
作者：
Bassolas, Aleix;Gallotti, Riccardo;Ramasco, Jose J.
公共交通是城市生活的基础设施。尽管其容量已满足日常需求，但当大量人群聚集参加示威、音乐会或体育赛事时，拥堵可能会加剧。在这项工作中，我们通过模仿系统中个人出行的程式化模型来研究公共交通网络的稳健性。我们发现，活动参与者和其他公民在后台进行日常出行所遭受的延误之间存在着规模关系。延迟是参与者数量和活动地点的函数。该模型在格中进行解析求解，证明了标度关系的存在及其指数与局部维度的联系。此后，在全球八个城市进行的广泛而系统的模拟表明，新提出的本地维度衡量标准解释了网络恢复中发现的指数。我们的方法可以动态探测交通网络的局部维度，并确定城市中最容易举办大型活动的地点。
Public transportation is a fundamental infrastructure for life in cities. Although its capacity is prepared for daily demand, congestion may rise when huge crowds gather in demonstrations, concerts or sport events. In this work, we study the robustness of public transportation networks by means of a stylized model mimicking individual mobility through the system. We find scaling relations in the delay suffered by both event participants and other citizens doing their usual traveling in the background. The delay is a function of the number of participants and the event location. The model is solved analytically in lattices proving the existence of scaling relations and the connection of their exponents to the local dimension. Thereafter, extensive and systematic simulations in eight worldwide cities reveal that a newly proposed measure of local dimension explains the exponents found in the network recovery. Our methodology allows to dynamically probe the local dimensionality of a transportation network and identify the most vulnerable spots in cities for the celebration of massive events.