Analysis of bike sharing system by clustering: the Vélib' case

Abstract

International audience; Bicycle sharing system has become more and more popular as it can help partly solve the problems such as CO2 over-emission and traffic congestion. Some systems have been operated for several years and the analysis work is very necessary for controlling and redesigning the system in purpose of getting better performances. In this paper we analyze the bike-sharing stations by clustering algorithms in order to mine the inner-station patterns, and these clustering results are essential for the system control and redesign. In this study, we take Vélib' bike sharing system in Paris as the study case.

Original document

The different versions of the original document can be found in:

• https://doi.org/10.1016/j.ifacol.2017.08.2430

• https://api.elsevier.com/content/article/PII:S2405896317332974?httpAccept=text/xml,

https://api.elsevier.com/content/article/PII:S2405896317332974?httpAccept=text/plain,

http://dx.doi.org/10.1016/j.ifacol.2017.08.2430 under the license https://www.elsevier.com/tdm/userlicense/1.0/

• https://hal.archives-ouvertes.fr/hal-01494490,

https://hal.archives-ouvertes.fr/hal-01494490/document,

https://hal.archives-ouvertes.fr/hal-01494490/file/IFAC%202017%20-%20clustering%20velib.pdf

• https://hal.archives-ouvertes.fr/hal-01494490/document,

https://www.sciencedirect.com/science/article/pii/S2405896317332974,

https://hal.archives-ouvertes.fr/hal-01494490,

https://academic.microsoft.com/#/detail/2766700587