State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China.
Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services and Research Institute for Smart Cities, Department of Urban Informatics, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, P.R. China.
PLoS One. 2019 Apr 16;14(4):e0215242. doi: 10.1371/journal.pone.0215242. eCollection 2019.
People's daily travels are structured and can be expressed as networks. Few studies explore how people organize their daily travels and which behavioral principles result in the choices of specific network types. In this study, we first reconstruct location networks and activity networks for numerous individuals from high-resolution mobile phone positioning data and define frequent networks as motifs. The results suggest that 99.9% of people's travels can be characterized by a limited set of location-based motifs and activity-based motifs. The results further reveal that the least effort principle governs the preferred motif choices through quantifying the rank-frequency properties. The scaling properties of distance characteristically impact motifs, and their scaling differences by node numbers and motif types coincide with the popularities of motifs, verifying the self-adaptions in motif choices; that is, although individuals travel with unique propensities, they always tend to choose the motif with the lowest consumption that satisfies their demand.
人们的日常出行是有组织的，可以用网络来表示。很少有研究探讨人们如何组织他们的日常出行，以及哪些行为原则导致了特定网络类型的选择。在这项研究中，我们首先从高分辨率的手机定位数据中为众多个体重建位置网络和活动网络，并将频繁出现的网络定义为基元。结果表明，99.9%的人的出行可以用有限的基于位置的基元和基于活动的基元来描述。结果进一步表明，通过量化等级频率特性，最小努力原则支配着首选基元的选择。距离的标度特性对基元有显著影响，其由节点数和基元类型决定的标度差异与基元的流行度一致，验证了基元选择的自适应性；也就是说，尽管个体出行的倾向是独特的，但他们总是倾向于选择消耗最低、能满足他们需求的基元。
