Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis

Haoran Zhang, Xuan Song, Yin Long, Tianqi Xia, Kai Fang, Jianqin Zheng, Dou Huang, Ryosuke Shibasaki and Yongtu Liang

Applied Energy, 2019, vol. 242, issue C, 138-147

Abstract: As a representation of smart and sustainable city development, bicycle-sharing system is one of the hottest topics in the domains of transportation, public health, urban planning, and so on. In this paper, a model is proposed for analyzing the potential reduction in emissions associated with the adoption of a bicycle-sharing system. Methods are proposed for extracting human travel modes from mobile phone GPS trajectories, together with a geometry-based probability model, to support particle swarm optimization. A comparison study is implemented to analyze the model’s computational efficiency. Based on the resulting optimal layout for the network of bicycle docking stations, and considering demand uncertainty, a multi-scenario integer linear programming model is proposed to optimize rebalancing procedures (i.e., moving bicycles between docking stations according to demand), to determine the detailed design-scale information required. Mobile phone GPS trajectories from approximately 3.7 million local mobilities are used to construct a case study for Setagaya Ward, Tokyo. The results show that, compared with the previous methods, the optimal layout solved by the proposed method could reduce emissions by a further 6.4% and 4.4%. With an increase from 30 to 90 bicycle stations, the adoption of bicycle-sharing can reduce CO2 emissions by approximately 3.1–3.8 thousand tonnes. However, emission reduction will maximally decrease by 21.26% after offset by bicycles production and rebalancing-generated emission.

Keywords: Bicycle-sharing; Geometry-based probability model; Particle swarm optimization; Rebalancing optimization; Potential emission reduction (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (15)

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DOI: 10.1016/j.apenergy.2019.03.119

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