Laura Bliss is CityLab’s West Coast bureau chief. She also writes MapLab, a biweekly newsletter about maps (subscribe here). Her work has appeared in The New York Times, The Atlantic, Los Angeles magazine, and beyond.
How easy is it to get around your part of town? Check the MobilityScore.
The ability to summon a ride from a phone can open pathways that never before existed. At least on paper.
That’s one insight drawn from MobilityScore, a map tool from TransitScreen, a company that develops dashboards for transportation data. MobilityScore aggregates data on different mobility options available at any given location in the 30 largest U.S. metros, and generates a 0-100 rating. Unlike other transit rating tools before it, its algorithm emphasize the benefit of having multiple modes.
Enter a location, and the MobilityScore will spit out a score that ranges from zero mobility options to a superb array. The scores are broken down across four shared modes of transportation: public transit, car share, ride-hailing, and bike sharing. MobilityScore measures data that reflect how reliable, frequent, and accessible these modes are.
For example, a spot in Penn Quarter, in the heart of downtown Washington, D.C., gets a MobilityScore rating of 100. Its score gets broken down like this:
That means that shared mobility in Penn Quarter is largely defined by its proximity to multiple transit stations within a quarter-mile walk, and dozens more within a full mile. The availability of bike share, car share, and ride-hailing options also helps bump up its overall score, although during the day, when transit is running most frequently and reliably, these options are weighed a little less heavily. When night falls, and trains and buses wind down, the availability of those alternatives becomes more important, while Penn Quarter’s overall score dips somewhat.
But Penn Quarter would never bottom out to a score of 62, which is how this spot in far-flung Deanwood, east of the Anacostia River and near the district’s northeast boundary, is scored by day. There, transit maps out like this:
There, transit stops are few, bike share drops to zero, and ride hailing becomes much more important in terms of reliability; presumably its weight will increase once transit service stops for the night. MobilityScore doesn’t only shift from day to night; TransitScreen is also gathering data in almost real-time from ride-hailing and car-sharing providers like Car2Go, ZipCar, Uber, and Lyft. The availability of their vehicles, almost down to the precise moment, is also reflected here.
That’s one important place where MobilityScore diverges from predecessors like Transit Score (which is produced by Walk Score, a separate company), which focuses more on the kinds of amenities that are available by transit, rather than the transit itself. Likewise, the in-depth transit analysis platform, AllTransit (these names, so easily confusable!), scores how well traditional transit modes get riders to jobs (it also looks at access to fixed bike share and car share).
Ryan Croft, TransitScreen’s cofounder and COO, says that their almost-real-time tool is “built to be future-proof (or at least future-compatible)”—it will be able to support autonomous vehicles, microtransit, and other emerging forms of mobility. Although MobilityScore gives traditional transit extra weight as the cheapest and generally most expansive option, it is more mode-agnostic than other rankings—all forms of mobility count.
Which is an interesting implication, from an equity standpoint. It’s true that, just as investments in fixed transit often pass by the low-income neighborhoods that need them most, the spread of bike sharing, car-sharing, and even ride-hailing has been uneven. On the other hand, the presence of Uber and Lyft in transit-poor and plain-poor neighborhoods can be transformative for people who need rides, now. This tool hints at why.