利用极值理论对个体最大日行程位移进行建模

Kaiqiang Xie, Lu Ma, Hui Xiong, Shasha Wu
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摘要

人口流动作为城市规划和交通预测的重要因素,近年来随着地理相关数据的出现而受到广泛关注。在本文中,我们基于近4000万个人的轨迹,使用极值理论(EVT)建立了关于个人最大日位移的人类流动性模型。发现最大日位移可以用广义帕累托分布(GPD)很好地拟合,并且与指数分布相比没有重尾。此外,我们还探讨了日最大流离失所者在不同性别和工作日的分布差异。分析结果表明,男性在周末的位移更大,个体的出行时间更长。
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Modeling Individuals' Largest Daily Trip Displacement using Extreme Value Theory
As a significant factor in urban planning and traffic forecasting, human mobility draws intensive attentions in recent years with the emergence of geo-related data. In this paper, we build models for human mobility with regards to individuals’ largest daily displacement using Extreme Value Theory (EVT) based on nearly 40 million individuals’ trajectories. It is found that the largest daily displacement can be well fitted by the Generalized Pareto Distribution (GPD) and is not heavy tailed compared to the exponential distribution. Besides, we also explored differences in distribution of the largest daily displacement according to gender and weekday. The analysis results indicate that male tend to have a larger displacement and individuals tend to travel longer on weekends.
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