Taxis are a way of life in New York City largely in part because that’s simply how transportation needs have been met for decades. The advent of ridesharing platforms like Lyft and Uber, however, has given those in the Big Apple options that are seemingly far superior to taxis in virtually every measurable category.
Just how much better are these modern solutions, you ask?
According to research recently published by MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), a fleet of just 3,000 four-passenger cars could serve 98 percent of taxi demand in New York City with an average wait time of 2.7 minutes compared to the nearly 14,000 taxis that currently service the city.
What’s more, MIT’s algorithm revealed that 95 percent of demand could be covered by just 2,000 10-person vehicles.
As Professor Daniela Rus notes, the key to reducing the number of vehicles on NYC roads is to transport more than one person at a time. This would result in fewer trips, less traffic, more free time for commuters and cleaner air, just to name a few benefits.
The algorithm also works in real-time to reroute vehicles based on incoming requests and can even proactively send idle cars to areas with high demand, a move that speeds up service by 20 percent, the professor said.
Rus adds that to the best of her 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 including taxis, vans and shuttles.
If nothing else, MIT’s work Illustrates how terribly inefficient NYC’s taxi systems really are.
Ridesharing image courtesy Crew, Flickr
https://www.techspot.com/news/67612-mit-study-shows-how-3000-ridesharing-vehicles-could.html
