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Chronicles

The story behind the story

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Study: between 2010 and 2016, traffic congestion in San Francisco grew by about 60%, with Uber and Lyft vehicles accounting for more than half of that increase

Andrew J. Hawkins / The Verge : Tweets: @violetblue Tweets: Violet Blue / @violetblue : No, we haven't been imagining the beatdown of our roads, constant traffic jams, worsening smog... New study finds Uber/Lyft triples travel time in SF, 20% of the cars are empty, 70% live outside SF, and the Uber/Lyft promise of reduced congestion is a lie. https://www.bizjournals.com/ ...

The Verge Andrew J. Hawkins

Context & Ripple Effects

The San Francisco findings land after years of dueling congestion studies. A 2015 Manhattan analysis found Uber displacing cabs without adding citywide congestion — a result the industry leaned on. Then a nine-city study argued services like UberPool were pulling riders off transit and out of walking trips, and Uber and Lyft countered with their own six-city research claiming their cars cause less congestion than personal vehicles.

This new SF-specific work cuts against both defenses: it attributes more than half of the city's ~60% congestion growth from 2010–2016 to ride-hail vehicles, with roughly 20% of them running empty and about 70% of drivers living outside the city. That matters because San Francisco is where the scale-up began — driver counts had already doubled year over year by 2015, and Uber's local revenue was then triple taxi revenues.

First-order effects

  • Uber and Lyft face direct evidence that their core product degrades travel times in their home market, undercutting the six-city self-published research they released months earlier as their congestion defense.

Second-order effects

  • City regulators now have a quantified basis for per-ride fees, empty-mile rules, or caps aimed specifically at ride-hail vehicles, and the transit-luring finding from the nine-city study gives transit agencies a reason to price or route against TNCs rather than treat them as complementary.

Third-order effects

  • If the pattern holds across dense cities, ride-hailing's regulatory model shifts from treating TNCs like taxis to pricing them like road-space users — with congestion data becoming the battleground between platform-funded studies and independent ones.

The trend: Ride-hailing's congestion impact is moving from contested claim to measured fact, giving cities the evidence base to regulate Uber and Lyft as traffic sources rather than taxi substitutes.