Exploring travel patterns and static rebalancing strategies for dockless bike-sharing systems from multi-source data: a framework and case study
This paper proposes a research framework for investigating the travel patterns of dockless bike-sharing and accomplishing the large-scale bike rebalancing at the city level. A case study involving Shanghai combines Global Positioning System (GPS)-based bike-sharing usage data and road network data. First, the spatiotemporal mobility patterns are analyzed visually; then community detection is used to divide the study area into management sub-areas according to the mobility characteristics of bike-sharing users; in addition, a clustering algorithm is used to identify virtual stations. On this basis, a heuristic algorithm is used to generate a rebalancing scheme that enables multiple visits to a given station. The results show that Shanghai can be divided into 28 bike-sharing management sub-areas. Static rebalancing based on the identified management sub-areas reduces the number and driving distance of rebalancing vehicles in use, which is a better outcome than that with a method based on administrative divisions.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
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Supplemental Notes:
- © 2022 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Lu, Chen
- Gao, Linjie
- Huang, Yuqiao
- Publication Date: 2023-4
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 336-349
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Serial:
- Transportation Letters: The International Journal of Transportation Research
- Volume: 15
- Issue Number: 4
- Publisher: Taylor & Francis
- ISSN: 1942-7867
- EISSN: 1942-7875
- Serial URL: http://www.tandfonline.com/toc/ytrl20/current
Subject/Index Terms
- TRT Terms: Algorithms; Bicycles; Global Positioning System; Travel patterns; Vehicle sharing
- Geographic Terms: Shanghai (China)
- Subject Areas: Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; Terminals and Facilities; Vehicles and Equipment;
Filing Info
- Accession Number: 01887475
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 17 2023 9:13AM