Department of Civil Engineering, Universidad Mariana, San Juan de Pasto, Colombia.
Instituto de Física, Universidad Nacional Autónoma de México, Ciudad de México, México.
PLoS One. 2019 Mar 6;14(3):e0213106. doi: 10.1371/journal.pone.0213106. eCollection 2019.
The understanding of human mobility patterns in different transportation modes is an interdisciplinary research field with a direct impact in aspects as varied as urban planning, traffic optimization, sustainability, the reduction of operating costs as well as the mitigation of pollution in urban areas. In this paper, we study the global activity of users in bike-sharing systems operating in the cities of Chicago and New York. For this transportation mode, we explore the temporal and spatial characteristics of the mobility of cyclists. In particular, through the analysis of origin-destination matrices, we characterize the spatial structure of the displacements of users. We apply a mobility model for the global activity of the system that classifies the displacements between stations in local and non-local transitions. In local transitions, cyclists move in a region around each station whereas, in the non-local case, bike users travel with long-range displacements in a similar way to Lévy flights. We reproduce the spatial dynamics by using Monte Carlo simulations. The obtained results are similar to the observed in real data and reveal that the model implemented captures important characteristics of the global spatial dynamics in the systems analyzed.
理解人类在不同交通模式下的移动模式是一个跨学科的研究领域,它对城市规划、交通优化、可持续性、降低运营成本以及减轻城市地区污染等方面都有直接的影响。在本文中,我们研究了在芝加哥和纽约市运营的自行车共享系统中用户的全球活动。对于这种交通模式,我们探索了自行车使用者的移动的时间和空间特征。特别是,通过对起点-终点矩阵的分析,我们描述了用户位移的空间结构。我们应用了一个用于系统整体活动的移动模型,将站点之间的位移分类为局部和非局部迁移。在局部迁移中,自行车使用者在每个站点周围的区域内移动,而在非局部情况下,自行车使用者则以类似于 Lévy 飞行的方式进行长距离位移。我们通过使用蒙特卡罗模拟来再现空间动态。得到的结果与实际数据中的观察结果相似,表明所实现的模型捕捉到了所分析系统中全球空间动态的重要特征。