What is it about?
What kind of infrastructure is there in areas where there are more public bike rentals? An analysis of German cities combined with Montreal and Chicago.
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Why is it important?
With a wider implementation of such an analysis, transport planners will have available a method that would help them to understand the factors that affect ridership of bike sharing systems, and thus ease and optimize the setting of coverage areas and placing stations where they may be most successful. This method can also show the validity and increase the reliability of measures, policies, and shared mobility projects
Perspectives
This paper helps to build demand models using only OpenStreetMap information. These models can help to search for the optimal location of stations when implementing a bike sharing system in a new area.
David Duran-Rodas
Technical University of Munich
Read the Original
This page is a summary of: Built Environment Factors Affecting Bike Sharing Ridership: Data-Driven Approach for Multiple Cities, Transportation Research Record Journal of the Transportation Research Board, June 2019, SAGE Publications,
DOI: 10.1177/0361198119849908.
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