2008/10/22 by Andreas Kaltenbrunner, Kaltenbrunner, Andreas, Rodrigo Meza +8
Computer Science · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #G.3 #H.3.3 #Human Mobility and Location-Based Analysis #Human-Computer Interaction (cs.HC) #Transportation Planning and Optimization #Urban Transport and Accessibility #cs.CY #cs.HC
paper · pdf · doi:10.48550/arxiv.0810.4187
10 pages, 8 figures
openalex publication_date 2008/10/22 · arxiv created 2008/10/23 · arxiv updated 2010/09/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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. The data was obtained by periodic mining of a KML-file accessible through the Bicing website. Although in principle very noisy, after some preprocessing and filtering steps the data allows to detect temporal patterns in mobility as well as identify residential, university, business and leisure areas of the city. The results lead to a proposal for an improvement of the bicing website, including a prediction of the number of available bikes in a certain station within the next minutes/hours. Furthermore a model for identifying the most probable routes between stations is briefly sketched.