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A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike

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Proceedings of the 2019 DigitalFUTURES (CDRF 2019)

Abstract

This paper is a study about visual analysis of spatiotemporal patterns of popular free floating bike sharing system (FFBSS) Mobike in Shanghai. Mining of over 32 million data points revealed strong cyclical variations on temporal patterns of usage between weeks; however weekday and weekend patterns differ. By using a geohash index based spatial data, we developed another visualization to encode the location of each shared bike ride. Through that, we found that the spatial distribution of Mobike shows a strong linear pattern, confirming that it is mainly used to solve the “last mile problem”. Emergence of vacant rectangles in the visualization informs the specific locations with intense traffic of checking in and out of individual bikes, providing an efficient tool for management of rebalancing.

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Correspondence to Ercument Gorgul .

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Gorgul, E., Chen, C. (2020). A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike. In: Yuan, P., Xie, Y., Yao, J., Yan, C. (eds) Proceedings of the 2019 DigitalFUTURES . CDRF 2019. Springer, Singapore. https://doi.org/10.1007/978-981-13-8153-9_13

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