For those who don’t know, TRB is the international mega-conference for transportation professionals. It’s held in Washington DC every January. This is the 95th year, making TRB older than the Winter Olympics, movies with sound, and Charles Lindbergh’s flight across the Atlantic.
Aside from being slightly overwhelming (10,000 people + 13 hours of sessions daily + introversion + information overload = one fried data geek), the conference is a treasure trove of data insights, especially regarding the interaction of the public and private sector around data. Here are some of the most interesting ideas that I came across.
Surprising absolutely no one, San Francisco is at the bleeding edge
Blessed with a neighbor like Silicon Valley, it would be hard for San Francisco to NOT be at the forefront of transportation data advancements. The San Francisco Municipal Transportation Agency (SFMTA) is developing an app for users to pick, in real-time, the best transportation modes and routes for that particular trip. The app uses public and private data to track travel times. SFMTA’s representative called the mode choices a “mobility accordion” ranging between Single Occupancy Vehicles (SOVs) and transit – bike shares, car shares, carpool services, scooter rentals, you name it. It even gamifies the travel experience by giving you “credits” for taking alternative modes.
Uber and Lyft were a big presence at TRB
Even in sessions that they didn’t attend, these two companies were a major part of the conversation. In the ultimate governmental sign of having “arrived”, they have their own acronym: TNCs, or Transportation Network Companies. Right now, that’s basically just a bureaucratic word for Uber and Lyft. In the future, it will come to encompass Shuddle, Bridj, and other shared transportation services that provide on-demand, third-party-driven (or even autonomous?) transportation for travelers.
One sad insight: public research on the effect of these companies lags SO HARD, you guys. It’s distressing to see the amount of thoughtful, diligent work put into researching and analyzing the impact of these travel changes – only to see it become near-obsolete by the time it gets published, two years later. That’s how fast Uber and Lyft, and their customers, are adapting. Perhaps these reports will have historic value, but in terms of helping transportation agencies respond operationally to these changes, it’s not fast enough.
Uber’s lead data scientist explained that a big hesitation about sharing their data, aside from the obvious value of the intellectual property, is his impression that it is nearly impossible to remove all identifying features of users: they cannot protect user privacy. Therefore they are only sharing with a limited number of vetted – and likely mostly academic – partners.
Meanwhile, closer to my home, University of Washington researchers Ryan Hughes and Donald W. MacKenzie found that there is no TNC “wait time penalty” in Seattle for those living in lower-income or predominantly minority neighborhoods. As in, a person in a primarily rich white neighborhood will get an Uber or Lyft in just about the same amount of time as a person in a poorer, more diverse neighborhood.
Waze
I missed the existence of this app somehow, so it’s possible that this is a revelation only to me. Newcomer Waze is a “community based traffic and navigation” app. The app pings users every 2 seconds to determine where they are, then uses anonymized, aggregated data from the smartphones of these “Connected Citizens” to determine best routes. It provides real-time re-routing around congestion, and push notifications for major closures.
Waze was on the scene to build more Public-Private Partnerships (PPPs). They’re looking for a two-way data exchange with governments: in return for access to their data, they want (planned) road closure data, real time incidents, school zones, HOV lane locations, etc. In pilot tests with cooperating public agencies, Waze has found that the majority of the time, in places where the Transportation Management Center (TMC – imagine a mini-NASA mission control for highways) is using their application, the TMCs are learning about incidents from Waze several minutes before it gets officially reported to the TMC. Waze might disrupt several other established traffic-data providers.
A few other observations:
A big complaint from multiple presenters at the conference regarding data sharing: public agencies’ legal departments. Even when practitioners and managers want to exchange data with the private sector, the legal department is a major barrier to data sharing.
Transportation agencies lament that they cannot attract the talent to do their data work in-house; the salaries and opportunities that they can offer technically proficient employees are not enough.