Uber, Lyft carpool services could reduce traffic by 75 percent, study says

For years, Uber and Lyft have been promising to save the world from traffic jams. A new study suggests they might actually be able to do it.

Carpool services such as UberPool and Lyft Line could reduce the number of vehicles on the road by 75 percent, according to findings released Tuesday by MIT’s Computer Science and Artificial Intelligence Laboratory.

That’s based on an algorithm researchers developed that found 3,000 four-passenger cars could serve 98 percent of taxi demand in New York City — compared to the nearly 14,000 taxis that currently operate there. And travelers could make the change without much inconvenience — the average wait time would be just 2.7 minutes.

“Instead of transporting people one at a time, drivers could transport two to four people at once, (resulting) in fewer trips, in less time, to make the same amount of money,” MIT professor Daniela Rus, who led the study, wrote in a news release. “A system like this could allow drivers to work shorter shifts, while also creating less traffic, cleaner air and shorter, less stressful commutes.”

The findings could help legitimize Lyft and Uber’s push toward shared rides, where multiple passengers going the same way are matched together in one car. Both companies are encouraging riders to use the relatively new carpooling services — which cost less than individual rides — as they try to make ride-hailing an everyday option for more people. Uber, for example, expanded UberPool into the East Bay in March (the service originally was only available to Bay Area riders within San Francisco).

As those services become more popular, it would be a major win for the Bay Area if they could reduce traffic. The region’s freeways have become increasingly congested, resulting in miserable commutes for many. A recent study found that Silicon Valley residents now face worse “megacommutes” — trips of 90 minutes or longer to work — than those in notoriously traffic-choked Los Angeles County.

The MIT algorithm calculated the potential impact of ride-hailing carpool services by creating a graph of all requests and all available vehicles, and then computing the best possible assignment for each vehicle. The algorithm also could automatically send idle vehicles to areas of higher demand, suggesting carpooling could have an especially pronounced impact on traffic once self-driving cars take off. Both Lyft and Uber are working on self-driving car programs, and hope eventually to deploy fleets of driverless cars.

“Ride-sharing services have enormous potential for positive societal impact with respect to congestion, pollution and energy consumption,” Rus wrote. “It’s important that we as researchers do everything we can to explore ways to make these transportation systems as efficient and reliable as possible.”

Photo: Traffic slows in the morning commute going westbound on Interstate 80 during the shutdown of the San Francisco-Oakland Bay Bridge Thursday, Aug. 29, 2013 in Berkeley, Calif. (Eric Risberg/AP)


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