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Smart city article details

Title	Practical Method To Improve Usage Efficiency Of Bike-Sharing Systems
ID_Doc	42618
Authors	Lee C.-H.; Lee J.-W.; Jung Y.
Year	2022
Published	ETRI Journal, 44, 2
DOI	http://dx.doi.org/10.4218/etrij.2021-0408
Abstract	Bicycle- or bike-sharing systems (BSSs) have received increasing attention as a secondary transportation mode due to their advantages, for example, accessibility, prevention of air pollution, and health promotion. However, in BSSs, due to bias in bike demands, the bike rebalancing problem should be solved. Various methods have been proposed to solve this problem; however, it is difficult to apply such methods to small cities because bike demand is sparse, and there are many practical issues to solve. Thus, we propose a demand prediction model using multiple classifiers, time grouping, categorization, weather analysis, and station correlation information. In addition, we analyze real-world relocation data by relocation managers and propose a relocation algorithm based on the analytical results to solve the bike rebalancing problem. The proposed system is compared experimentally with the results obtained by the real relocation managers. 1225-6463/$ © 2022 ETRI.
Author Keywords	bike prediction; bike relocation; bike-sharing system; machine learning; smart city

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