An optimization approach for equitable bicycle share station siting

Bicycle share systems are becoming an increasingly popular feature of many urban areas across the United States. While these systems aim to increase transit mode options as well as overall bicycle ridership, bike share programs also face challenges and criticisms related to density and inequitable distribution of services. Key factors in the success of bicycle share include high station density as well as services that reach a variety of neighborhoods, though many current systems do not reach low-income areas. Equitable station distribution therefore appears to be a complex problem to address. We propose utilizing spatial analytics, including GIS and spatial optimization, to help site bicycle share stations across an urban region. Specifically we seek to apply a covering model to assess how many bicycle stations are needed, and where they should be located, so no user would have to travel too far for access. The city of Phoenix, Arizona, is used as a case study to illustrate the coverage and access tradeoffs possible through different investment strategies. Accordingly, for a given investment level, the set of stations is identified that provides the best access to the designated bike path network for the greatest number of potential users. Further, tradeoff options that differentially favor either network or population coverage are possible, and can be identified and evaluated through the proposed analytical framework.