Plug Into New Ideas
Your Transit Directions Just Got a Little Bit Better
Rocky Mountain Institute (RMI) just convened a group of data experts to improve the information we use to make choices about how we travel. Imagine you are visiting a city for the first time and you want to go downtown. If you pull out your smartphone and punch a destination into your mapping app of choice (Google Maps, Apple Maps, Transit App, etc.), you’ll probably see a few different transportation options: driving, public transit, walking, biking, and often ridehailing services like Uber. Because a complex set of constraints—such as time, cost, ease of parking, and environmental impact—can affect travel choices, presenting a compelling set of options to a traveler requires good information, and a lot of it.
The data behind that set of options is what we call interoperable transit data. RMI is collaborating with organizations from across the transportation sector to improve the availability and quality of information on transportation options that have a smaller environmental impact than driving alone. With better information, travelers will find it easier to access, and compare, modes of transportation that will get them quickly to their destination in a cost-effective way.
A Working Group to Improve the GTFS
RMI convened a group of organizations to tackle a first challenge: improving the General Transit Feed Specification (GTFS). The GTFS is the current data specification in which public transit agencies in the U.S. and around the world post their static (i.e., not real-time) data. This data includes the geographic data for bus and train routes, stops, timetables, fares, and the like. Interpreting this data is essential to how your favorite mapping app is able to display transit directions.
Although the GTFS has been adopted in much of the world, and is even used as a powerful tool in international development by the World Bank, inconsistencies and gaps remain in how transit agencies feed information into the GTFS. This results in a lot of work for application developers, and sometimes in an incomplete and inconsistent experience for travelers. The lack of a clear set of guidelines also makes it more challenging and often more expensive for transit authorities to produce these feeds. RMI, with our collaborators in a working group, set out to solve these problems by publishing a document titled the GTFS Data Best Practices.
The GTFS Best Practices
The best practices document, published in February 2017, is the culmination of months of brainstorming, workshops, surveying, and testing from some of the most active developers and thought leaders in GTFS. The work leading to this document stems from a workshop RMI convened in San Francisco in 2015. The publication provides general guidance (such as naming conventions and feed maintenance) for transit agencies, examples of properly formatted feeds, and procedures for tricky situations such as “loop” and “lasso” routes.
We hope that releasing these best practices is a first step toward creating a more open and clear data specification that is easier to adopt for public transit agencies, and quicker to implement for application developers. Ultimately, our goal is to help provide a clear and seamless user experience for travelers. The availability of this information will make it easier for people to choose public transportation who might otherwise default to driving a car. This will result in less traffic congestion, cleaner air, and reduced carbon emissions.
Building Toward a Consortium
With the initial success of the work on the GTFS, the working group recognized its unique opportunity to tackle thorny problems in transportation data that demand various viewpoints and experience. To this end, RMI is developing a governance structure to transition the working group into a durable and efficient consortium that can continue to improve transportation data across modes and operators. The consortium is considering an array of subsequent missions, including creating a specification to capture the often-convoluted and opaque fare structures of public and private transportation services; enhancing real-time transit data specifications to describe short-term service changes; investigating improved APIs and standards for data from ridehail companies (aka transportation network companies, or TNCs); and developing data specifications to link transit with other complementary modes, like bikeshares and park and rides.
In an increasingly connected and automated world, information and data infrastructure will be as important for transportation as concrete is today. But the generation of vast amounts of data is not enough; the data must also be organized and precise. By forming a consortium of leading developers, agencies, and transit providers, we can ensure that the information for a more connected transportation age is accessible and open, allows people to make well-informed travel decisions to make our lives more painless and more equitable, and allows us to have a lighter touch on our planet.
Guest author Jackson Crane is a doctoral student studying energy systems at Stanford University and was previously an associate in the Mobility Practice at RMI.