Analysis of the temporal profile of use of bikesharing stations in the Bikesampa system

Authors

DOI:

https://doi.org/10.58922/transportes.v31i1.2825

Keywords:

Bikesharing, Temporal pattern, Clusters, Spatial correlation

Abstract

Bikesharing systems have gained popularity over the years and now face the challenge of being responsive and of meeting the growing demand. Thus, understanding the temporal pattern of bikesharing trips is paramount. This study examined data from Bikesampa (a fixed-station system operating in the Brazilian city of São Paulo) and applied k-means clustering to stations according to the hourly demand of pickups and returns. The results revealed three clusters: (i) balanced, (ii) unbalanced, with higher rates of bike pickup in the morning and (iii) unbalanced, with higher rates of bike return in the morning. A spatial autocorrelation analysis showed that cluster membership was not randomly distributed over space, suggesting an association with characteristics of the urban environment, and indicating that the system may require different rebalancing strategies depending on the stations location. Such understanding can help guide the development of operational strategies and user incentive policies to improve the efficiency of bikesharing systems.

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Imagem da capa, volume 31, número 1, 2023

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Published

2023-02-27

How to Cite

Malta Baracat, T. ., Strambi, O., & Lavieri, P. . (2023). Analysis of the temporal profile of use of bikesharing stations in the Bikesampa system. TRANSPORTES, 31(1), 2825. https://doi.org/10.58922/transportes.v31i1.2825

Issue

Vol. 31 No. 1 (2023)

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Artigos

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Copyright (c) 2023 Thais Malta Baracat, Orlando Strambi, Patrícia Lavieri

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