Determining Once and for All How the ‘Gig Economy’ Impacts Transit


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Cities like Sacramento are helping pilot a new measure of interaction between travel modes.

Cities like Sacramento, California want to know how their residents ways of getting around interact, so mobility analytics company StreetLight Data aims to provide them with a measure this fall.

The San Francisco-based company’s Multimodal Measurement Initiative, which begins its second wave of pilots this summer, won’t simply show how many people walk from point A to point B.

Behavior of personal vehicles, public transit, pedestrians, bikers, commercial trucks, and the “gig economy”—from Lyft to Uber Eats—will all be taken into account.

“What we care about is how they affect other parts of the transportation system and the economy,” Laura Schewel, CEO of StreetLight Data, told Route Fifty.

Schewel said city officials have long wanted the data to help them figure out things like where to put bike lanes that will encourage more biking, but that requires knowledge of driving behavior on prospective streets.

The gig economy, particularly ride hailing services, adds an additional layer of complexity, as cities have long suspected they contribute to congestion on the roads. But the data science is hard as is, and data on the industry is hard to come by.

“And it’s because Uber and Lyft won’t share, and I understand why they won’t share,” Schewel said. “But there needs to be some form of measurement.”

StreetLight Data needed partners already collecting data on transportation network companies, or TNCs, as well as pedestrians and bikers, to help “triangulate metrics” through “clever validation studies.” So the company partnered with Sacramento and the State Smart Transportation Initiative on an initial case study.

The M2 Initiative is also developing a working group of universities, agencies and consulting firms to further its efforts.

A second wave of pilots this summer is about expanding the geographic scope of the findings and adding gig driving metrics to the pedestrian and bike metrics from the first pilot, which tried to get at when people were specifically using those modes for exercise as opposed to getting around.

Often data is only collected on walking, running or biking when a person is killed doing those activities, Schewel said, when cities really want to know if they’re meeting their green transportation mandate or how they can reduce congestion and demand for cars while still getting people around.

“There are only a couple thousand counters, and they don’t even work that well,” Schewel said. “So we’re totally blind on bicycle and pedestrian data.”

Gig economy information is even more scarce. Are Uber drivers idling and halting traffic? Are TNCs like Uber and Lyft helping or hurting public transit?

“Nobody knows; there are a huge array of beliefs,” Schewel said. “Nobody has even the beginnings of an iota of an answer.”

Dave Nyczepir is a News Editor at Government Executive’s Route Fifty and is based in Washington, D.C.

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