01623046

Component

https://doi.org/10.3141/2662-02

Bikeshare systems with docking stations have gained popularity in cities throughout the United States—and have increased from six programs with 2,300 bikes in 2010 to 74 systems with 32,200 bikes in 2016. Even though bikeshare systems generate a wealth of data about bicycle checkout and check-in locations and times at docking stations, virtually nothing is known about routes and activities undertaken between checkout and check-in. Such information could greatly enhance expansion of bikeshare systems, placement of new docking stations, and location of new bike lanes and paths. In pursuit of such information, the District Department of Transportation, Washington, D.C., placed GPS trackers on 94 Capital Bikeshare (CaBi) bikes in the spring of 2015. On the basis of these data, this geographic information system analysis distinguished riders by type of CaBi membership, identified popular routes, analyzed bicycle infrastructure use, and examined stops and dwelling times at places of interest. Results showed strong differences in trip attributes between types of membership. Trips taken by short-term users were longer in distance, slower than long-term users’ trips, and concentrated in and around the National Mall, whereas long-term users’ trips were concentrated in mixed-use neighborhoods. Short-term users rode 12% of their miles on dedicated bicycle infrastructure, 61% in parks, and 27% on roadways with motorized traffic, whereas for long-term members the percentages were 33%, 17%, and 50%, respectively. On the basis of the routes taken in this study, potential locations were recommended for bicycle infrastructure improvements and new bikeshare stations.

01656974

17-01167

English

pp 12–21

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309460415

Digital/other

Figures (8) ; References (29) ; Tables (2)

Bicycles; Data mining; Global Positioning System; Routes; Travel patterns; Trip generation; Vehicle sharing

Capital Bikeshare; District Department of Transportation

Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors

TRIS, TRB, ATRI

Dec 8 2016 10:21AM

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• Impact of Bike Facilities on Residential Property Prices
• Impacts of Level of Traffic Stress on Bikeshare Ridership in the Case of Capital Bikeshare in Montgomery County, Maryland
• Investigation of Alternative Bicycle Pavement Markings with the Use of a Bicycle Simulator
• Keep ’Em Separated: Desire Lines Analysis of Bidirectional Cycle Tracks in Montreal, Canada
• Low-Stress Bicycle Network Mapping: The District of Columbia’s Innovative Approach to Applying Level of Traffic Stress
• Mind the Gap: Assessing the Impacts of Bicycle Accessibility and Mobility on Mode Share in Washington, D.C.
• Observations of Public Bikesharing: Experiences from Ningbo, China
• The Reach of Bicycling in Rural, Small, and Low-Density Places
• Typologies of Urban Cyclists: Review of Market Segmentation Methods for Planning Practice