Measuring the Pulse of the City through Shared Bicycle Programs

Jon E. Froehlich · Joachim Neumann · Nuria Oliver

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Human Mobility and Location-Based Analysis Urban Transport and Accessibility Smart Cities and Technologies

Abstract

City-wide urban infrastructures are increasingly reliant on networked technology to improve and expand their services. As a side effect of this digitalization, large amounts of data can be sensed and analyzed to uncover patterns of human behavior. In this paper, we sense and analyze data from a new type of urban infrastructure called shared bicycling. We provide a spatio-temporal analysis of six weeks of usage data from Barcelona's shared bicycling system called Bicing. We show how these digital traces can be used to uncover daily routines, cultural influences and the role of time and space in city dynamics. I.

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References

2008Understanding individual human mobility patterns 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis 2008Digital Footprinting: Uncovering Tourists with User-Generated Content

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2021Intelligent management of bike sharing in smart cities using machine learning and Internet of Things 2020Understanding intra-urban human mobility through an exploratory spatiotemporal analysis of bike-sharing trajectories 2018Identifying Urban Functional Zones Using Public Bicycle Rental Records and Point-of-Interest Data 2022Unravel the spatio-temporal patterns and their nonlinear relationship with correlates of dockless shared bikes near metro stations 2012Modeling User Perception of Public Bicycle Services 2013A Dynamical Network View of Lyon’s Vélo’v Shared Bicycle System 2018Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems 2016Predicting critical conditions in bicycle sharing systems

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