首页> 外文期刊>Nature >Understanding individual human mobility patterns
【24h】

Understanding individual human mobility patterns

机译:了解个人的出行方式

获取原文
获取原文并翻译 | 示例
       

摘要

Despite their importance for urban planning, traffic forecasting and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time-independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling.
机译:尽管它们对于城市规划,交通流量预测以及生物和移动病毒的传播具有重要意义,但由于缺乏监测个人在时间上可分辨的位置的工具,我们对管理人体运动的基本规律的理解仍然有限。在这里,我们研究了100,000个匿名手机用户的轨迹,这些用户的位置被跟踪了六个月。我们发现,与流行的Levy飞行和随机游走模型所预测的随机轨迹相反,人类轨迹显示出高度的时空规律性,每个人都具有与时间无关的特征行进距离,并且具有显着的概率返回一些人迹罕至的地方。在校正了行进距离和每个轨迹的固有各向异性的差异之后,各个行进模式崩溃为单个空间概率分布,这表明尽管行进历史不同,但人类仍遵循简单的可复制模式。这种出行方式固有的相似性可能会影响由人口流动导致的所有现象,从流行病预防到应急响应,城市规划和基于主体的建模。

著录项

  • 来源
    《Nature》 |2008年第7196期|p.779-782|共4页
  • 作者单位

    Center for Complex Network Research and Department of Physics, Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然科学总论;
  • 关键词

  • 入库时间 2022-08-18 02:55:54

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号