Algorithm does real-time, city-wide ridesharing
Anyone who's ever been stuck in stop-and-go traffic would be happy to tell you that congestion is a waste of time. But the true scale of the waste is difficult to comprehend. It's estimated that congestion costs the US one percent of its annual GDP, as people waste otherwise productive hours and fuel sitting in their vehicles. That doesn't even consider all the pollution it creates.
Despite those numbers, most people wouldn't choose to use options that cut congestion, like public transit or ridesharing. In many cases, that's because these alternatives require giving up some autonomy, as you can't necessarily go where you want whenever you want.
A paper in this week's PNAS suggests that doesn't have to be the case. Using a real-world database of fully autonomous travel—a week's worth of New York City taxi rides—the authors demonstrate an algorithm that can service travel needs in real time with minimal waits for a ride. The result would be far fewer cars on the road. Even with standard cabs, only a quarter of today's taxi fleet would be required to service all the ride requests.
