Cities get creative to measure the ‘Uber Effect’ (CityLab)

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Ride-hailing companies are cagey on all-important trip data. So researchers are finding clever workarounds.

They’d cut back on traffic, ease air pollution, and complement public transit. Or so they said. But the effects of Uber, Lyft, and other transportation network companies (“TNCs,” in wonk-speak) are proving more complicated on city streets. In New York City, rapid growth in on-demand vehicles roving the roads—with and without passengers—is contributing to markedly slower traffic, as numerous analyses of Taxi and Limousine Commission data by Bruce Schaller, a transportation consultant and former NYC DOT official, have shown.

As the old chestnut goes, cities can’t manage what they can’t measure. But because Uber and Lyft carefully guard raw trip data, the kind of analyses Schaller produces is hard to produce in many cities. At the 97th annual meeting of the Transportation Research Board this week, Schaller moderated a panel of experts from San Francisco, Chicago, New York City, and Boston on the importance of capturing on-demand mobility data—and how researchers are getting creative to do it.

San Francisco is by some measures the third-most congested city in the nation, but public officials found that ride-hailing companies weren’t all that helpful in figuring out exactly why. “There is lots of happy talk about collaboration,” said panelist Joseph Castiglione, the deputy director for technology, data, and analysis at the San Francisco County Transportation Authority. “But the type of information they claimed to be willing to share was not entirely useful.”

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Written by Long Branch Mike