基于时空轨迹数据的出行特征挖掘方法

发布时间：2018-05-04 03:40

本文选题：城市交通 + 信息技术　；参考：《交通运输系统工程与信息》2014年06期

【摘要】：在车联网应用发展的背景下,许多城市的私家车和出租车上安装了配备GPS设备的智能终端,产生着大量的时空轨迹数据.为挖掘这些数据蕴含的驾驶员出行特征,本文以北京市出租车时空轨迹数据为例,基于时空GIS的视角提出并实现了驾驶员居住地挖掘方法和作息规律性分析方法.样本实验结果一方面展示了驾驶员居住地空间分布,另一方面表明作息规律性总相似度在0.6 1之间的驾驶员数量较多,占到了总数的73.75%.通过本文方法挖掘的信息可为出租车的管理提供辅助决策,方法同样适用私家车时空轨迹数据的挖掘,对私家车出行规律的研究和掌握更有意义.
[Abstract]:Under the background of the development of the application of car networking, many private cars and taxis in many cities have installed intelligent terminals equipped with GPS equipment, which produces a large amount of space-time trajectory data. In order to mine the characteristics of drivers' travel in these data, this paper takes the spatio-temporal track data of Beijing taxi as an example, and puts forward and realizes the mining method of drivers' residence and the analysis method of the regularity of working and rest based on the perspective of spatio-temporal GIS. On the one hand, the sample results show the spatial distribution of drivers' residence, on the other hand, it shows that the number of drivers with the general similarity of work and rest regularity between 0.6 and 1 is more, accounting for 73.75% of the total. The information mined by this method can provide auxiliary decision for taxi management. The method is also applicable to the mining of private cars' space-time track data, which is more significant for the study and mastering of private car travel rules.
【作者单位】：北京建筑大学测绘与城市空间信息学院;现代城市测绘国家测绘地理信息局重点实验室;中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室;
【基金】：现代城市测绘国家测绘地理信息局重点实验室开放基金项目(20111216N) 北京市优秀人才培养资助个人项目(2011D005017000005)
【分类号】：U495

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