Probabilistic Forecasts of Bike-Sharing Systems for Journey Planning

Nicolas Gast · Guillaume Massonnet · Daniël Reijsbergen · Mirco Tribastone

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Urban Transport and Accessibility Transportation Planning and Optimization Transportation and Mobility Innovations

Abstract

We study the problem of making forecasts about the future availability of bicycles in stations of a bike-sharing system (BSS). This is relevant in order to make recommendations guaranteeing that the probability that a user will be able to make a journey is sufficiently high. To do this we use probabilistic predictions obtained from a queuing theoretical time-inhomogeneous model of a BSS. The model is parametrized and successfully validated using historical data from the Vélib' BSS of the City of Paris.

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References

2007Strictly Proper Scoring Rules, Prediction, and Estimation 2000Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications 1998Queueing Networks and Markov Chains 2015Bikeshare: A Review of Recent Literature 2010Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system 2009Sensing and predicting the pulse of the city through shared bicycling 2012Large-Scale Vehicle Sharing Systems: Analysis of Vélib'2014Incentives and redistribution in homogeneous bike-sharing systems with stations of finite capacity

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