In 2011, there were more than 150 million taxi trips taken in New York City that began or ended in Manhattan, traveling inside 13,586 registered cabs. Taxis ferried passengers from Grand Central Station to near Union Square some 73,000 times, and from Union Square to Grand Central Station 94,000 more. New Yorkers on the Upper West Side took thousands of seemingly walkable, short taxi rides just a few blocks up Broadway. Elsewhere, 584 trips — that's more than one a day — ran from the New York Stock Exchange to what looks an awful lot like the doorstep of Per Se.
Taken in the aggregate, all of these numbers raise an important question.
"Are people from the same place going to the same destination at the same time?" asks Michael Szell, a researcher with MIT's Senseable City Lab. "If so, could they share rides?"
Of course, this kind of cab sharing does happen on an intimate scale, as say, strangers walk off a plane together or strike up a conversation at a cab stand. And ride-sharing is now much more common using private cars, through apps like Sidecar or Lyft. But what would happen if we combined those two ideas, if we could optimize the entire taxi network in New York as if it were a single, integrated, all-seeing system? In other words, as if it knew those two bankers were both on their way to Per Se.
The Senseable City Lab submitted a public records request to the New York City Taxi and Limousine Commission for all its data on those 150 million trips from 2011. They've mapped it in gorgeous, interactive detail here, as part of the HubCab project unveiled today. Even more usefully, though, they've made a startling calculation with all that data: nearly 80 percent of all of those trips could have been shared if passengers were willing to travel no more than three minutes out of their way.
If we assume that each trip carries one person (the data doesn't specify this), and that two trips can reasonably be combined in the back seat of one cab, that means a totally optimized taxi network in New York would produce 40 percent fewer trips, a similar drop in emissions, and far less traffic. That's 40 percent of all those trips that would just never need to be made.
The HubCab map uses the 2011 data to translate those potential financial and energy savings between any two pickup and dropoff pairs in the city. Zoom in far enough on the map, and each pickup is represented by a yellow dot and a dropoff by a blue one (except where many dots have blended together). Zoom out, and arterial roads where people commonly hunt for taxis appear yellow; blocks where cabs drop off more people than they pick up look blue.
Those 40 percent savings are based on a lot of assumptions, including the idea that 100 percent of taxi riders would be willing to share. Szell acknowledges that that's not likely.
"There are psychological barriers," he says. "There are many people who don’t want to sit next to a stranger in a cab. In practice, this percentage would be much lower than 100 percent, maybe more like 10 percent in the beginning."
But in a city like New York, if even 10 percent of cab riders were willing to participate in such a system, they would still constitute a critical mass that could make a difference. In the scenarios that the Senseable City Lab has modeled, the efficiency benefits from cab-sharing kick in quickly even when only a small share of riders are willing to join. This might not be true in less populous, cab-dependent cities. But New York makes for a great illustration.
"Our goal was to provide some kind of mathematical assessment of the potential to sharing," Szell says, "so policymakers can be convinced that this makes sense."
From here, a lot of questions remain as to how a city could actually implement this math. You'd need some kind of central dispatch system coordinating cabs that are now operated by different companies. You'd need a consumer-facing app that acts as a portal into the system. And you'd probably need to change the fare structure to satisfy cab drivers who won't be happy about seeing their business cut way down.
Perhaps in this theoretical system, individual rides would be worth more to cab drivers than they are now – but they'd still be cheaper to individual riders willing to double up. Imagine two people each paying $10 for identical but separate rides, while together they'd pay $15. If a city could strike the right financial balance, in theory, riders would save money, streets would be less congested, and whole cities would save on carbon emissions.