Uncovering commuting flows in Bike Sharing Systems

Abstract

Drawing on the observed regularity of typical trips, this study proposes a method for identifying commuting patterns without using the individual identifiers of public bike-share users. The approach combines an analysis of trip duration distributions, mixture models and logistic regression based on the posterior probabilities of belonging to the ___fast' and ___typical' journey categories.