In the mid-nineteenth century, the French poet Charles Baudelaire wrote about a new kind of city-dweller -- the "flâneur," or urban stroller, a "botanist of the street" who "walks the city in order to experience it." He'd be surprised at how we walk the city today. Armed with GPS-enabled smartphones that pinpoint our locations on a constantly shifting, data-saturated city map, we're no longer explorers but tacticians, calculating the quickest route between points A and B. Now it looks like the same tactical revolution is coming to the world of taxicabs. Passengers are now able to use smartphone software to share cabs and save money (costing cabbies business in the process). Meanwhile, as Marisa Plumb explains in the IEEE Spectrum, an engineering magazine, researchers are mining GPS data to optimize cabbie performance. An international team of software engineers is figuring out how to make drivers better at finding passengers, asking which strategies work best for the top-performing drivers.
What's his strategy?
On the passenger side, ride-sharing apps like CabCorner, available for Apple's iPhone, let prospective passengers with similar destinations find one another on the street to share a cab. The service, which launched in 2009, aims to save passengers money. But such services also reduce the number of fares available for cab drivers, who work in a low-margin, high fixed cost business, and are, therefore, just barely profitable. (That's why Boston cab drivers have negotiated higher fares.) Software like CabCorner is based on GPS, which lets a central computer system figure out where prospective passengers are located and where they might meet up. GPS, however, can be used in the opposite direction: to tell drivers where and how they ought to pick up passengers. Plumb, reporting on a recent "pervasive computing" conference in Seattle, explains how researchers have used data from a GPS-enabled taxi fleet in Hangzhou, China to analyze taxi pickup strategy.
Cabbies work within a complicated decision matrix: every passenger picked up and dropped off presents a decision-point. Take a passenger to a distant neighborhood, or leave him standing on the corner? Drive back to the city center, or stay put, save gas, and hope for a new fare? Those decisions unfold differently depending on time of day and location. But staying put, it turns out, generally pays less than roaming around: the study, Plumb writes, shows that "the top 10 performing drivers -- those who had the highest number of passenger pickups overall -- consistently chose to hunt for passengers or drive back to a busy area after drop-offs." Daqing Zhang, a researcher, says that the next step is to figure out which routes these constantly-driving cabbies ought to take to pick up the most passengers. Those recommendations could eventually be built directly into taxicab GPS systems.
But a city full of driver-optimized taxicabs, while it's more efficient for the drivers, might be less efficient for passengers waiting in or going to less busy areas. They may, in turn, look to software like CabCorner to game the system. As another group of researchers argues, a fleet of data-driven taxicabs, though more efficient in some ways, might actually end up being less efficient overall (or, as they put it, adversely effecting "socially motivated system optimization"). It seems inevitable that, someday soon, "intelligent recommendation systems" will be built into taxicab GPS displays, and into consumer smartphones. But whether passengers' and drivers' systems will work together or against one another is anybody's guess. Today, inefficiency is a natural part of the taxi system, shared equally by everyone. Tomorrow, it may be a hot potato, tossed from cabbies to drivers and back again.
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Leon Neyfakh is the staff writer for Ideas. Amanda Katz is the deputy Ideas editor. Stephen Heuser is the Ideas editor.
Guest blogger Simon Waxman is Managing Editor of Boston Review and has written for WBUR, Alternet, McSweeney's, Jacobin, and others.
Guest blogger Elizabeth Manus is a writer living in New York City. She has been a book review editor at the Boston Phoenix, and a columnist for The New York Observer and Metro.
Guest blogger Sarah Laskow is a freelance writer and editor in New York City. She edits Smithsonian's SmartNews blog and has contributed to Salon, Good, The American Prospect, Bloomberg News, and other publications.
Guest blogger Joshua Glenn is a Boston-based writer, publisher, and freelance semiotician. He was the original Brainiac blogger, and is currently editor of the blog HiLobrow, publisher of a series of Radium Age science fiction novels, and co-author/co-editor of several books, including the story collection "Significant Objects" and the kids' field guide to life "Unbored."
Guest blogger Ruth Graham is a freelance journalist in New Hampshire, and a frequent Ideas contributor. She is a former features editor for the New York Sun, and has written for publications including Slate and the Wall Street Journal.
Joshua Rothman is a graduate student and Teaching Fellow in the Harvard English department, and an Instructor in Public Policy at the Harvard Kennedy School of Government. He teaches novels and political writing.