计算机应用 ›› 2015, Vol. 35 ›› Issue (9): 2453-2456.DOI: 10.11772/j.issn.1001-9081.2015.09.2453

• 网络与通讯 • 上一篇    下一篇

二维空间上基于呼叫详细记录数据的用户移动性分析

石立兴, 胡访宇   

  1. 中国科学技术大学 信息科学与技术学院, 合肥 230027
  • 收稿日期:2015-04-15 修回日期:2015-05-08 出版日期:2015-09-10 发布日期:2015-09-17
  • 通讯作者: 石立兴(1987-),男,福建龙岩人,硕士研究生,主要研究方向:移动通信数据分析,shilx@mail.ustc.edu.cn
  • 作者简介:胡访宇(1955-),男,浙江永康人,教授,主要研究方向:通信网、智能信息系统、通信信号处理。
  • 基金资助:
    安徽省科技计划项目(1201b0403021)。

Users' mobility analysis based on call detail record in two-dimensional space

SHI Lixing, HU Fangyu   

  1. School of Information Science and Technology, University of Science and Technology of China, Hefei Anhui 230027, China
  • Received:2015-04-15 Revised:2015-05-08 Online:2015-09-10 Published:2015-09-17

摘要: 针对当前基于呼叫详细记录(CDR) 研究用户移动性主要局限于移动距离、回旋半径等一维尺度,且该尺度不能准确描述移动范围的问题,提出在二维空间上用覆盖移动轨迹的凸包面积来描述用户的移动范围,用群体移动向量分析人群的移动行为。首先,设计了一种基于经纬度建立二维平面笛卡尔坐标系的方法。该方法结合墨卡托投影与半正矢公式得到散点间方位与距离,并依此确立散点在平面坐标系的坐标;然后,基于该坐标系计算了覆盖用户一天内移动轨迹的凸包及其面积,并统计其分布;最后,对所有用户的移动向量分时段作累积,分析群体移动向量在一天内的变化。实验结果表明,在180 km范围内,新坐标所计算的方位角与由墨卡托投影下确定的结果平均偏差0.037°,点间距离与由半正矢公式得到的结果平均偏差0.102%,可以很好地保持散点间的方位与距离关系。覆盖移动轨迹的凸包面积满足幂律分布,并与移动距离有较高的相关性。群体移动向量的变化展现了人群移动的潮汐现象,而且为发掘用户所在区域与周边地区的联系提供新的视角。

关键词: 坐标转换, 呼叫详细记录, 移动性, 轨迹凸包, 移动向量

Abstract: Since recent studies on users' mobility based on Call Detail Record (CDR) mainly use metrics in one-dimensional space, such as the travel distance and the radius of gyration which can not exactly describe the scope of users' mobility, the Area of the Convex Hull Covering a user's daily Trajectory (ACHCT) was applied to investigate users' mobility scale in two-dimensional space, and the mobility vector was introduced to study the mobility of the crowd. Firstly, a method was designed to set up two-dimensional Cartesian coordinates based on latitude and longitude coordinates. The method applied the Mercator projection and the haversine formula to calculate the bearing and distance between scattering points, based on which the coordinates of points in the plane coordinates were determined. Then, based on the coordinates, the convex hulls covering users' daily trajectories were calculated and the distribution of the areas of all convex hulls was analyzed. Finally, the mobility vectors of agglomerated de-identified callers were accumulated respectively in different time segments and the changes in a day were analyzed. The experimental results show that, within the scale of 180 km, the average deviations of bearing angle and distance calculated with the new coordinates are 0.037° and 0.102%, compared with those calculated with Mercator projection and haversine formula. The new coordinates can maintain the distance and bearing between points well. ACHCT follows a power-law distribution and has a strong correlation with the travel distance. The changes of the crowd's mobility vector, show the tidal phenomenon of the crowd's travel and give a new sight to discover the correlation between areas where users reside and those nearby.

Key words: coordinate transform, Call Detail Record (CDR), mobility, convex hull of trajectory, mobility vector

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