01697844

Component

Public bikesharing models are growing across the U.S., including docked, dockless, and e-bike models. This paper focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform the authors' analysis, the authors used two datasets for February 2018 of Ford GoBike (docked) and JUMP (dockless e-bikesharing) trips in San Francisco. The authors employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) transportation equity framework. The authors found that dockless e-bikesharing trips were longer in distance and duration than station-based trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with .8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The model results suggest that JUMP users travel to lower-density destinations, and GoBike users were largely traveling to work. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The 20 STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing 21 systems in areas of the city where high-job density and bike facility availability converge with 22 older- and lower-income populations.

This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.

19-02761

English

0000-0003-1645-2530

21p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; Maps; References; Tables

Bicycles; Case studies; Choice models; Electric vehicles; Equity; Travel behavior; Vehicle sharing

San Francisco (California)

Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation; Vehicles and Equipment

Transportation Research Board Annual Meeting 2019 Paper #19-02761

TRIS, TRB, ATRI

Dec 7 2018 9:39AM