Bikeshare Ridership in Suburban Systems

Suburban bike share systems and smaller bike share systems within larger multi-city present a new opportunity to study factors that affect ridership. Previous research and models that predict ridership in bike share systems have focused on larger urban areas. The three suburban cities of Redwood City, Palo Alto and Mountain View known as the Peninsula cities, as part of the San Francisco Bay Area Bike Share system record low ridership rates of 0.22 trips per bike per day compared to San Francisco of 2.51. When compared to other suburban cities internal trips as part of Capital Bike Share in Washington D.C. and Hubway in Boston, the Peninsula cities show similar ridership rates. A regression model was developed based on service area and station density to surmise how system ridership can change if these variables are increased. It shows that every square mile added to the system area can expect a return in the order of 0.17 trips per bike per day. As well, if density is increased by 1 station per square mile, the resulting impact on ridership is smaller, 0.017 trips per bike per day. This research shows that in smaller more suburban bike share systems, system size is a more important variable than station density in predicting ridership.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Co, Sean
    • Witte, Adrian
    • Machell, Erin
    • Enns, Lisa
    • Judelman, Belinda
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 13p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01623445
  • Record Type: Publication
  • Report/Paper Numbers: 17-05506
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 25 2017 9:30AM