系统仿真学报 ›› 2019, Vol. 31 ›› Issue (12): 2829-2836.doi: 10.16182/j.issn1004731x.joss.19-FZ0327

• 仿真应用工程 • 上一篇    下一篇

基于兴趣点聚类的无桩共享单车时空模式分析

张芳1, 陈彬1, 汤杨华2, 董健1, 艾川1, 邱晓刚1   

  1. 1. 国防科技大学系统工程学院,湖南 长沙 410073;
    2. 上海栖芯信息科技有限公司,上海 200082
  • 收稿日期:2019-05-20 修回日期:2019-07-16 发布日期:2019-12-13
  • 作者简介:张芳(1995-),女,安徽六安,硕士生,研究方向为系统仿真。
  • 基金资助:
    国家重点研发计划重点专项资金(2017YFC1200300), 国家自然科学基金(71673292,71673294), 国家社会科学基金(17CGL047), 广东省大数据分析与舆情仿真重点实验室

Spatiotemporal Mode Analysis of Urban Dockless Shared Bikes based on Point of Interests Clustering

Zhang Fang1, Chen Bin1, Tang Yanghua2, Dong Jian1, Ai Chuan1, Qiu Xiaogang1   

  1. 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China;
    2. Shanghai Neweco Information Technology Co., Ltd, Shanghai 200082, China
  • Received:2019-05-20 Revised:2019-07-16 Published:2019-12-13

摘要: 城市无桩共享单车发展迅猛,其方便快捷、经济高效的特点受到人们的推崇。它们产生的数字足迹揭示了城市范围内人们在时间和空间上的活动,使利用共享单车对城市中人们的活动进行定量分析成为可能。利用采集的北京市无桩共享单车数据,提出了一种基于城市兴趣点聚类的方法,对城市空间进行划分,构建城市共享单车的流动网络,并从不同的角度分析单车流动的时空模式。本文的研究有助于了解城市居民的出行特点,帮助城市相关管理人员设计和规划城市交通管理体系。

关键词: 无桩共享单车, 兴趣点, 聚类, 流动网络, 时空模式

Abstract: The city’s dockless shared bikes have developed rapidly, and its features of convenience, economy and efficiency have been widely welcomed. The digital footprint they generate reveals the movement of people in time and space within the city, which makes it possible to quantify the activities of people in the city using shared bikes. In this paper, based on the collected shared bikes data of Beijing, a clustering method based on the point of interests is proposed to divide the urban space, so as to construct a mobile network of urban shared bikes, and analysis the spatiotemporal mode of bike flow from different perspectives. The research in this paper is helpful to understand the characteristics of urban residents' travel and help urban managers to design and plan the urban traffic management systems.

Key words: dockless shared bikes, point of interests, clustering, mobile network, spatiotemporal mode

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