Data Analysis and Optimization for (Citi)Bike Sharing

David B. Shmoys

164 citations0/0 files storedProceedings of the AAAI Conference on Artificial Intelligence

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Urban Transport and Accessibility Vehicle Routing Optimization Methods Transportation and Mobility Innovations

Abstract

Bike-sharing systems are becoming increasingly prevalent in urban environments. They provide a low-cost, environmentally-friendly transportation alternative for cities. The management of these systems gives rise to many optimization problems. Chief among these problems is the issue of bicycle rebalancing. Users imbalance the system by creating demand in an asymmetric pattern. This necessitates action to put the system back in balance with the requisite levels of bicycles at each station to facilitate future use. In this paper, we tackle the problem of maintaing system balance during peak rush-hour usageas well as rebalancing overnight to prepare the systemfor rush-hour usage. We provide novel problem formulationsthat have been motivated by both a close collaborationwith the New York City bike share (Citibike) and a careful analysisof system usage data. We analyze system data to discover the best placement of bikes tofacilitate usage. We solve routing problems forovernight shifts as well as clustering problems for handlingmid rush-hour usage. The tools developed from this research are currently in daily use at NYC Bike Share LLC, operators of Citibike.

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References

2010Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system 2012Optimizing the location of stations in bike-sharing programs: A GIS approach 2010Strategic design of public bicycle sharing systems with service level constraints 2012Large-Scale Vehicle Sharing Systems: Analysis of Vélib'2013Models for Effective Deployment and Redistribution of Bicycles Within Public Bicycle-Sharing Systems

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