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

Authors

Zhang Fang, 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Bin Chen, 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Yanghua Tang, 2. Shanghai Neweco Information Technology Co., Ltd, Shanghai 200082, China;
Dong Jian, 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Chuan Ai, 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Xiaogang Qiu, 1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;

Abstract

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.

Recommended Citation

Fang, Zhang; Chen, Bin; Tang, Yanghua; Jian, Dong; Ai, Chuan; and Qiu, Xiaogang (2019) "Spatiotemporal Mode Analysis of Urban Dockless Shared Bikes based on Point of Interests Clustering," Journal of System Simulation: Vol. 31: Iss. 12, Article 32.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0327
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss12/32

First Page

2829

Revised Date

2019-07-16

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0327

Last Page

2836

CLC

TP391.9

Recommended Citation

Zhang Fang, Chen Bin, Tang Yanghua, Dong Jian, Ai Chuan, Qiu Xiaogang. Spatiotemporal Mode Analysis of Urban Dockless Shared Bikes based on Point of Interests Clustering[J]. Journal of System Simulation, 2019, 31(12): 2829-2836.

DOI

10.16182/j.issn1004731x.joss.19-FZ0327