Modelling the scaling properties of human mobility
Modelling the scaling properties of human mobility
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DOI：
10.1038/nphys1760
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发表时间：
2010-10-01
期刊：
影响因子：
19.6
通讯作者：
Barabasi, Albert-Laszlo
中科院分区：
文献类型：
--
作者：
Song, Chaoming;Koren, Tal;Barabasi, Albert-Laszlo
个体人类的移动轨迹具有跳跃大小和等待时间的厚尾分布特征，这表明连续时间随机游走（CTRW）模型与人类移动性具有相关性。然而，人类的踪迹几乎不是随机的。鉴于人类移动性的重要性，从流行病建模到交通预测以及城市规划，我们需要能够解释个体人类移动轨迹统计特征的定量模型。在此，我们利用通过手机轨迹获取的有关人类移动性的经验数据，来表明CTRW模型的预测与经验结果存在系统性冲突。我们引入了两条支配人类移动轨迹的原则，从而能够为个体人类移动性建立一个统计上自洽的微观模型。该模型解释了经验上观察到的标度律，还使我们能够分析性地预测大多数相关的标度指数。
Individual human trajectories are characterized by fat-tailed distributions of jump sizes and waiting times, suggesting the relevance of continuous-time random-walk (CTRW) models for human mobility. However, human traces are barely random. Given the importance of human mobility, from epidemic modelling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile-phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model accounts for the empirically observed scaling laws, but also allows us to analytically predict most of the pertinent scaling exponents.