Modeling Bike Sharing System using Built Environment Factors

Tien Dung Tran · Nicolas Ovtracht · Bruno Faivre d’Arcier

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

Abstract

This paper aims to present a modeling of bike sharing demand at station level in the city of Lyon. Robust linear regression models were used in order to predict the flows of each station. The data used in this project consists of over 6 million bike sharing trips recorded in 2011. The built environment variables used in the model are determined in a buffer zone of 300 meters around each bike sharing station. In order to estimate the bike sharing flow, we use the method of linear regression during the peak periods of a weekday. The results show that bike sharing is principally used for commuting purposes by long term subscribers while short term subscriber's trips purposes are more varied. The combination between bike sharing and train seems to be an important inter-modality. An interesting finding is that student is an important user of bike sharing. We found that there were different types of bikesharing usage which are influenced by socio-economic factors depending on the period within the day and type of subscribers. The present findings could be useful for others cities which want to adopt a bikesharing system and also for a better planning and operation of existing systems. Further, the solutions to encourage the use of bikesharing will be various depending on type of subscribers. The approach in this paper can be useful for estimating car-sharing demand.

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References

2010Bikesharing in Europe, the Americas, and Asia 2009Bike-sharing: History, Impacts, Models of Provision, and Future 2014How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal 2014Health effects of the London bicycle sharing system: health impact modelling study 2009Sensing and predicting the pulse of the city through shared bicycling 2013Station-Level Forecasting of Bikesharing Ridership 2013Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach 2010Characterizing the speed and paths of shared bicycle use in Lyon

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2019Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City 2018Built environment and public bike usage for metro access: A comparison of neighborhoods in Beijing, Taipei, and Tokyo 2021Electric bike-sharing services mode substitution for driving, public transit, and cycling 2020Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems

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