An MIT developed algorithm shows that 3,000 four-passenger cars could replace 98% of all cabs in NYC. Carpooling could prove to be the best way to eliminate traffic congestion and limit CO2 emission, not only in urban areas.
A recent study conducted by MIT scientists yielded an algorithm that showed how carpooling could be the way to eliminate some of the traffic congestion presently faced by big urban areas. According to researchers, 3,000 four-passenger cars could serve 98 percent of taxi demand in New York City, with an average wait-time of only 2.7 minutes. The team also found that 95 percent of demand would be covered by just 2,000 ten-person vehicles, compared to the nearly 14,000 taxis that currently operating in NYC.
The research, led by Javier Alonso-Mora and published in the Proceedings of the National Academy of the Sciences looked at how ride-sharing services are already transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. But researcher found that provider like Uber or Lyft face some limitations in their operations and came up with a mathematical model and an algorithm that applies to fleets of autonomous vehicles and also incorporates re-balancing of idling vehicles to areas of high demand.
The new system, developed by MIT scientists allows requests to be re-matched to different vehicles. It can also analyze a range of different types of vehicles to determine, where or when a 10-person van would be of the greatest benefit. It works by creating a graph of all request and then generating a second graph for all possible combinations using a specified method to compute the best assignment of vehicles. After the vehicles are assigned, the algorithm can recalibrate the remaining idle vehicles by sending them to higher-demand areas.
According to scientists involved in the study, carpooling, taking efficiency and reliability into account, could offer solutions for tackling some of the important problems facing our cities like congestion, pollution and energy consumption.