A Framework for Estimating Bikeshare Origin Destination Flows Using a Multiple Discrete Continuous System

This current study identifies two choice dimensions for capturing the bike share system demand: (1) station level demand and (2) how bike flows from an origin station are distributed across the network. A linear mixed model is considered to estimate station level demand while a multiple discrete continuous extreme value (MDCEV) model to analyze flows distribution is employed. The data for the analysis is drawn from New York City bikeshare system (CitiBike) for six months from January through June, 2017. For the analysis, the authors examine demand and distribution patterns on a weekly basis. A host of exogenous variables including trip attributes, socio-demographic attributes, bicycle infrastructure attributes, land use and built environment, temporal and weather attributes are considered. The model estimation results offer very intuitive results for origin demand and multiple discrete destination choice models. The authors validated the model by predicting trips to destined stations and found that predicted model performs well for high demand destinations. This analysis will allow bike sharing system planners and operators to better evaluate and improve bikeshare systems.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Dey, Bibhas Kumar
    • Anowar, Sabreena
    • Eluru, Naveen
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 9p

Subject/Index Terms

Filing Info

  • Accession Number: 01697420
  • Record Type: Publication
  • Report/Paper Numbers: 19-02351
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:27AM