Abstract:Bikesharing has gained popularity over the years and now faces the challenge to be responsive and meet the growing demand. Thus, understanding the temporal pattern of bikesharing trips is paramount. This study examined data from the Bikesampa bikesharing system (a fixed station system operating in the Brazilian city of São Paulo).First, a k-means clustering was applied to group bikesharing stations according to hourly demand of bike pick-ups and returns. The results revealed three clusters of stations with wel… Show more
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