Automotive

Could 3,000 ride-sharing cars replace nearly 14,000 New York cabs?

Could 3,000 ride-sharing cars replace nearly 14,000 New York cabs?
The MIT team believes its new system is a big step forward
The MIT team believes its new system is a big step forward
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The MIT team believes its new system is a big step forward
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The MIT team believes its new system is a big step forward

New York City, a place known for yellow taxis and traffic congestion, could soon feature a lot less of both with a shift toward ride-sharing services, a new study has found. Scientists at MIT have devised a new algorithm that suggests almost all of the city's 14,000 or so taxis could be replaced by just 3,000 ride-sharing vehicles, all without significantly impacting travel time.

Led by Professor Daniela Rus from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), the team developed an algorithm that works in real-time to to redirect cars according the incoming requests.

Based on data from three million taxi rides, the algorithm begins by creating a graph of all ride requests and all vehicles. A second graph is then created of all the possible trip combinations and a method the team calls "integer linear programming" is used to determine the most efficient ride assignments. As the cars are assigned rides, the algorithm then sends remaining idle cars to high-demand areas, which apparently speeds up overall service by 20 percent.

"A key challenge was to develop a real-time solution that considers the thousands of vehicles and requests at once," she says. "We can do this in our method because that first step enables us to understand and abstract the road network at a fine level of detail."

While carpooling is not a new concept, and has been modernized by Uber and Lyft through the use of smartphone data in recent years, the team believes its new system is a big step forward. Where existing systems might require one user to be waiting en route for another for the service to work, or for all ride requests to be lodged before a route can be created, the new system, which Rus describes as an "anytime optimal algorithm," is purported to have more flexibility.

"To our knowledge, this is the first time that scientists have been able to experimentally quantify the trade-off between fleet size, capacity, waiting time, travel delay, and operational costs for a range of vehicles, from taxis to vans and shuttles," says Rus. "What's more, the system is particularly suited to autonomous cars, since it can continuously reroute vehicles based on real-time requests."

The researchers say the algorithm could see 3,000 four-passenger cars serve 98 percent of taxi demand in New York City, with an average wait time of 2.7 minutes. And it can also take into account which vehicle size is the most appropriate for the route in question – the team found that 95 percent of the city's taxi demand could be handled by 2,000 10-person vans.

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

The research will be published this week in the journal Proceedings of the National Academy of the Sciences.

Source: MIT

6 comments
6 comments
oldguy
Is anyone thinking about the thousands of people that will be unemployed with the advent of autonomous trucks and sharing cars etc? Will they all sit alongside the roads and watch as we, the 'elites' slide past in comfort? Maybe we should working from the top down with these huge companies that own trucks and cars. The highest paid should be replaced first. So a computer could easily replace a half dozen CEO's....
CAVUMark
RIP "Driving Experience"
Bruce H. Anderson
Taking more than one passenger, or a rotating series of passengers may be more efficient, but there is always the element of time. One multi-stop trip would take less overall time that several individual trips (such is the nature of mass transit) but the time for each passenger's trip may take longer. Maybe the passengers will not mind the extra time for the extra distance/stops, but perhaps the reduced congestion will mean faster traffic flow, so it could be a wash.
f8lee
Well, @oldguy, welcome to technological advancement - which has forever replaced people, since the days of the wheel. And @CAVUMark, your sentiment is already true by way of autonomous driving - when self-driving cars are ubiquitous then the car companies will suffer - since brand and "driving experience" will mean nothing to people. After all, when you fly commercial, do you decide what flight to take based on the manufacturer of the airplane? So we shall all just summon a ride when needed and personal car ownership will just fade away. RIP shade tree mechanics, too.
habakak
Well said, F8Lee. People inevitably will complain about change. Autonomous cars will be a more economical and efficient use of societies resources as well as safer. People will have to adapt. Nobody complains about the farming jobs that we lost in the past 150 years. They forget that people struggled back then to catch up with the change too, but here we are, a much better off and richer society with healthier and longer lives. NYC did not have a famous yellow taxi cab fleet 100 years ago, so why should it have one 25 years from now? All things come to an end.
ReneVishney
From the CEO of Qwykr Inc. Actually, I think there simulation is flawed. There are 14,000 medallions, but never 14,0000 taxis on the street. So there basic conclusion is a fairy tale. Today, the NYC wait time on Uber & Lyft averages 20 minutes at peak times. There are, according to Uber, 20,000 Uber cars on the street at any given time. [Which is a difficult number to verify] Uber already offers, disassociated riders a special rate. Uber is also already doing peak load identification modeling for their drivers. The simulation they describe is done with lots of missing data. It is a great example of statisticians are great liars.
For Don Rector CEO Qwykr By Rene Vishney Qwykr