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Modeling Bike Sharing System using Built Environment Factors

Author

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  • Tien Dung Tran

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Ovtracht

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Bruno Faivre d'Arcier

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

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.

Suggested Citation

  • Tien Dung Tran & Nicolas Ovtracht & Bruno Faivre d'Arcier, 2015. "Modeling Bike Sharing System using Built Environment Factors," Post-Print halshs-01474166, HAL.
    • Handle: RePEc:hal:journl:halshs-01474166
    DOI: 10.1016/j.procir.2015.02.156
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01474166
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    References listed on IDEAS

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    1. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future," Institute of Transportation Studies, Working Paper Series qt79v822k5, Institute of Transportation Studies, UC Davis.
    2. Shaheen, Susan A & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present and Future," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6qg8q6ft, Institute of Transportation Studies, UC Berkeley.
    3. Jesus Gonzalez-Feliu & Joëlle Morana, 2010. "Collaborative transportation sharing: from theory to practice via a case study from France," Post-Print halshs-00460923, HAL.
    4. Yves Crozet & Aurélie Mercier & Nicolas Ovtracht, 2012. "Accessibility: a key indicator to assess the past and future of urban mobility," Chapters, in: Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), Accessibility Analysis and Transport Planning, chapter 15, pages 263-279, Edward Elgar Publishing.
    5. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
    6. Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), 2012. "Accessibility Analysis and Transport Planning," Books, Edward Elgar Publishing, number 14718.
    Full references (including those not matched with items on IDEAS)

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