Analysis of the spatiotemporal riding modes of dockless shared bicycles based on tensor decomposition

ABSTRACT

Studies on the riding modes of shared bicycles have aimed to heighten the understanding of cycling characteristics. This paper analyzes the spatiotemporal riding modes of shared bicycles based on tensor decomposition in Beijing, China. Two third-order tensors are constructed for the origin and destination points of shared bicycles in the day, hour, and space dimensions. Three factor matrices explicitly reveal two modes, three modes, and six modes in the day dimension, hour dimension, and space dimension, respectively. The relationships among the different modes in the three dimensions are demonstrated in an interaction table. Further, the density for different types of points of interest (POIs) are calculated to further analyze the potential riding purpose for different riding modes. Notably, the main POI types for the areas of O2 and D2 modes are consistent with the areas of D3 and O3 modes, which reflects the tidal characteristics of the commuting activities of shared bicycles. The main functional areas are inferred according to the riding modes and POIs, which enables verification of the correctness of the obtained riding modes to some extent. By method comparison, tensor decomposition shows the advantage of being able to reveal the spatiotemporal modes among multiple dimensions.

KEYWORDS:

• Dockless shared bicycles
• bicycle riding
• spatiotemporal modes
• tensor decomposition
• Tucker

Acknowledgments

We thank the editor and anonymous reviewers who provided helpful suggestions on ways to improve the paper.

Disclosure statement

No potential conflicts of interest are reported by the authors.

Data and codes availability statement

The data and codes that support the findings of this study are available in Github with the identifier: https://github.com/SharingBikeNNU/Riding-Modes_Tucker and freely available at the open geographic modeling and simulation platform (OpenGMS, http://geomodeling.njnu.edu.cn/Bicycle-sharing).

Additional information

Funding

This work was supported by the NSF of China [41622108]; National Natural Science Foundation of China [41671385, 41622108, and 41871178]; Priority Academic Program Development of Jiangsu Higher Education Institutions [164320H116]; The Qing-Lan Project of Nanjing Normal University.

Notes on contributors

Min Cao

Min Cao is an associate professor in the School of Geography, Nanjing Normal University, Nanjing, China. Her research interests include geographic information system, geographic information science, and virtual geographic environments. Email: [email protected].

Mengxue Huang

Mengxue Huang received her master degree in the School of Geography, Nanjing Normal University. She works in Norinco Group North Information Control Research Academy Croup Co., Ltd. Her research interests include geographic information system, geographic information science, and virtual geographic environments.

Shangjing Ma

Shangjing Ma is a master student in the School of Geography, Nanjing Normal University. Her research interests include geographic information system, geographic information science, and virtual geographic environments. Email: [email protected].

Guonian Lü

Guonian Lü is a professor in the School of Geography, Nanjing Normal University, Nanjing, China. His research interests include geographic information system, geographic information science, and virtual geographic environments. Email: [email protected].

Min Chen

Min Chen is a professor in the School of Geography, Nanjing Normal University, Nanjing, China. His research interests include geographic information system, geographic information science, and virtual geographic environments. Email: [email protected].