Browsing by Subject "Bikeshare"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Public bike stations in Indianapolis: a location allocation study
    (2018-02) Cooper, Samuel D.; Banerjee, Aniruddha; Wilson, Jeffrey S.; Lulla, Vijay
    Location Allocation, rooted in Operations Research and Mathematical programming, allows real world problems to be solved using optimization (based on mathematics and science) and equity principles (based on ethics). Finding nearest facilities for everyone simultaneously is a task solved by numerical and algebraic solutions. Bikeshare as a public good requires equitable allocation of bikeshare resources. Distance, as an impediment, can be minimized using location allocation algorithms. Since location allocation of this kind involves large numbers, sophisticated algorithms are needed to solve them due to their combinatorically explosive nature (i.e. as ‘n’ rises, solution time rises at least exponentially – sometimes called ‘Non Polynomial Time-Hard’ problems). Every day, researchers are working to improve such algorithms, since faster and better solutions can improve such algorithms and in turn help improve our daily lives.
  • Thumbnail Image
    Item
    Visitor bikeshare usage: tracking visitor spatiotemporal behavior using big data
    (Taylor & Francis, 2020-09-11) Buning, Richard J; Lulla, Vijay
    Bikeshare programs are a popular, convenient, and sustainable mode of transportation that provide a range of benefits to urban communities such as reduction in carbon emissions, decreased travel times, financial savings, and heightened physical activity. Although, tourists are especially inclined to use bikeshare to explore a destination as the programs are a convenient, cheap, flexible, and an active alternative to vehicles and mass transit little research or attention has focused on visitor usage. As such the current study investigated the spatial-temporal usage patterns of bikeshare by visitors to an urban community using GPS based big data (N = 353,733). The results revealed differential usage patterns between visitors and local residents based on user provided ZIP Codes using a 50 mile geometric circular buffer around the urban destination. The visitors and residents significantly varied on numerous trip behaviors including route selection, time of rental, checkout/check-in locations, distance, speed, duration, and physical activity intensity. The user patterns uncovered suggest visitors primarily use bikeshare for leisure based urban exploration, compared to residents’ primary use of bikeshare to be public transportation related. Implications for bikeshare, urban planning, and tourism management are provided aimed at delivering a more sustainable and richer visitor experience.