Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
464951 | Pervasive and Mobile Computing | 2010 | 12 Pages |
Abstract
This paper provides an analysis of human mobility data in an urban area using the amount of available bikes in the stations of the community bicycle program Bicing in Barcelona. Based on data sampled from the operator’s website, it is possible to detect temporal and geographic mobility patterns within the city. These patterns are applied to predict the number of available bikes for any station some minutes/hours ahead. The predictions could be used to improve the bicycle program and the information given to the users via the Bicing website.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Andreas Kaltenbrunner, Rodrigo Meza, Jens Grivolla, Joan Codina, Rafael Banchs,