Uber and Lyft are more than just a nuisance to taxi and private-hire firms: They play a vital role in reducing traffic, pollution, and energy usage.

A new MIT study suggests ride-sharing services could eliminate 75 percent of the vehicles on public roads, without significantly impacting travel time.

Led by professor Daniela Rus of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), researchers developed an algorithm that found 3,000 four-person cars could serve 98 percent of taxi demand in New York City, with an average wait time of 2.7 minutes.

This theory only works, however, if people are willing to truly share their ride—not just with a stranger behind the wheel, but with strangers in the backseat.

"Instead of transporting people one at a time, drivers could transport two to four people at once, results in fewer trips, in less time, to make the same amount of money," Rus said in a statement.

MIT is also eyeing buses and shuttles, which can carry up to 10 people at a time.

"A system like this could allow drivers to work shorter shifts, while also creating less traffic, cleaner air, and shorter, less stressful commutes," Rus said.

The algorithm, according to MIT, creates two graphs—one with all requests and all vehicles, one with all possible trip combinations. The computer then assigns cars to trips, and can rebalance idle drivers by sending them to higher-demand areas.

"Ride-sharing services have enormous potential for positive societal impact with respect to congestion, pollution and energy consumption," Rus said. "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."

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