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arXiv 0912.4371physics.soc-phphysics.data-an
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佛罗伦萨地区微观GPS数据中的城市流动性统计规律

Statistical Laws in Urban Mobility from microscopic GPS data in the area of Florence

Armando Bazzani, Bruno Giorgini, Sandro Rambaldi, Riccardo Gallotti, Luca Giovannini

摘要:

统计物理学在社会系统中的应用主要涉及对宏观规律的探索,这些规律可以从时间或空间平均的实验数据中推导出来,假设系统处于稳定状态。主要目标之一是找到统计定律与微观性质之间的联系:例如,理解微观相互作用的性质或指出相互作用网络的存在。概率论表明,在热力学极限下存在少数几类平稳分布,因此问题是统计物理学方法是否能够纳入社会系统的复杂性质。我们已经分析了一个大型的GPS数据库,在佛罗伦萨市区的单车移动性,获得统计规律的路径长度,活动停机时间和活动度。我们还表明,简单的一般假设的微观行为可以解释存在的静态宏观法律,与一个通用的功能描述的分布。我们的结论是,理解系统的复杂性需要微观演化的动态数据库,这允许解决小的空间和时间尺度,以研究瞬态。

英文摘要:

The application of Statistical Physics to social systems is mainly related to the search for macroscopic laws, that can be derived from experimental data averaged in time or space,assuming the system in a steady state. One of the major goals would be to find a connection between the statistical laws to the microscopic properties: for example to understand the nature of the microscopic interactions or to point out the existence of interaction networks. The probability theory suggests the existence of few classes of stationary distributions in the thermodynamics limit, so that the question is if a statistical physics approach could be able to enroll the complex nature of the social systems. We have analyzed a large GPS data base for single vehicle mobility in the Florence urban area, obtaining statistical laws for path lengths, for activity downtimes and for activity degrees. We show also that simple generic assumptions on the microscopic behavior could explain the existence of stationary macroscopic laws, with an universal function describing the distribution. Our conclusion is that understanding the system complexity requires dynamical data-base for the microscopic evolution, that allow to solve both small space and time scales in order to study the transients.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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