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Rapidly expanding mobile apps for crowd-sourcing bike data to new cities : final report.
  • Published Date:
    2017-03-01
  • Language:
    English
Filetype[PDF-1.53 MB]


Details:
  • Publication/ Report Number:
  • Resource Type:
  • Edition:
    Final report
  • Abstract:
    Cities such as San Francisco, Atlanta, and Portland are using novel methods of data collection to learn more about the use of their bicycle

    infrastructure. These data can help transportation planners better design or upgrade bicycle facilities. San Francisco created an open-source

    project, Cycle Tracks, a mobile app used to collect bike path data from bicyclists’ smartphones. These data then were used in the SF-CHAMP

    travel demand model to forecast how attractive Bike Facility A would be compared to Bike Facility B to understand the potential mode shifts

    that could occur with implementation of bike infrastructure, and to better understand the impact of new SF bike infrastructure on bicyclist travel

    behavior. A similar project, Cycle Atlanta, was implemented in Atlanta, GA, and was based on the Cycle Tracks open-source code, as was

    ORcycle for Portland, OR. These methods of gathering data from the public via mobile apps are referred to as “crowd-sourcing.”

    Whereas open-source crowd-sourcing mobile apps can provide a wealth of information to transportation planners, there is at least one major

    obstacle to deploying these projects in new cities: software engineers for iOS and Android must modify and re-deploy these apps for each city.

    As a result, deploying these apps in new cities can be very costly, which limits adoption and removes opportunities for innovation based on data

    collected from such apps.

    This project takes the first steps towards helping to overcome the barriers to wide-scale adoption of bike data crowd-sourcing mobile apps by

    creating a proof-of-concept “multi-region” architecture, allowing cities to share the same set of mobile apps on the Android and iOS apps stores

    while setting up their own server specific to their geographic area. This solution can reduce the cost of deployment by leveraging the mobile

    apps that already exist, rather than each city needing to modify and launch its own version of the apps. Future work should focus on developing

    a brand identity of these multi-region apps, including a possible partnership with existing organizations that have deployed existing apps (e.g.,

    Georgia Tech for Cycle Atlanta, San Francisco County Transportation Authority for Cycle Tracks) to further test and release the multi-region

    improvements as updates to their existing applications. Use of the standardized Open311 format to report issues can also be examined, along

    with leveraging other open-source transportation applications such as OneBusAway to give users additional incentive and value to continue to

    contribute trip data.

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