And a related piece :
http://www.wired.com/magazine/2010/0..._traffic/all/1
The Man Who Could Unsnarl Manhattan Traffic
spreadsheet linK:
http://www.nnyn.org/kheelplan/BTA_1.1.xls
By Felix Salmon Email Author
May 24, 2010 |
12:00 pm |
Wired June 2010
Photo: Peter Yang
Charles Komanoff says he has the solution to New York's congestion problem—and he’s got the math to prove it.
Photo: Peter Yang
The walk to Charles Komanoff’s favorite lunch spot, a patisserie two blocks from his office in Manhattan’s Financial District, usually takes a couple of minutes. But on this December afternoon, Komanoff has spotted a truck from the grocery-delivery service FreshDirect. His eyes widen and his steps quicken as he approaches the orange and green refrigerated vehicle. Within seconds, he’s peppering the driver—politely but insistently—with questions. What route did you take to get here? How many deliveries do you make per trip? How often do you double-park? Do you leave the engine running?
Komanoff assures the driver that he is not a corporate spy. He’s a traffic expert who has taken up the Borgesian task of re-creating, in precise detail, the economic and environmental impact of every single car, bus, truck, taxi, train, subway, bicycle, and pedestrian moving around New York City. And to do that he needs data. Lots of data. Which is why even the shortest walk can turn into an hours-long fact-finding mission.
When he finally gets back to his office, Komanoff will use this interview to inform his magnum opus, the Balanced Transportation Analyzer (.xls), an enormous Excel spreadsheet that he’s been building for the past three years. Over the course of about 50 worksheets, the BTA breaks down every aspect of New York City transportation—subway revenues, traffic jams, noise pollution—in an attempt to discover which mix of tolls and surcharges would create the greatest benefit for the largest number of people.
Komanoff’s spreadsheet, which he has posted online, calculates how new fees and changes to existing tolls affect traffic at different times of day. It calculates which costs are borne by city dwellers and which by suburbanites. It calculates how long it takes passengers to dig for change and board buses. And it allows any user to adjust dozens of different variables—from taxi surcharges to truck tolls—and measure their impact. The result is a kind of statistical SimCity, an opportunity to play God (or at least Robert Moses) and devise the perfect traffic policy.
Komanoff is a dyed-in-the-wool stats geek, and the BTA demonstrates his faith in data. By measuring the problem—the amount of time and money lost in traffic every year—we can begin to solve it, he says. We can turn the knobs on the entire transportation system to maximize efficiency. Komanoff’s model suggests a world in which everything from subway fares to bridge tolls can be precisely tuned throughout the day, allowing city planners to steer traffic flow as quickly and smoothly as a taxi driver tooling his cab down Broadway on a quiet Sunday morning.
It’s hard for Komanoff—a fit, if slightly unkempt, 62-year-old—to conceal his pride in this spreadsheet. “It’s a mansion with 50 rooms, and each one relates to all the others,” says Komanoff, who shares his Tribeca apartment with his wife, two kids, and a Steinway piano. “Maybe this is how Mozart felt when he was scoring Don Giovanni.”
Komanoff’s masterpiece has impressed municipal traffic planners from New York to Paris to Guangzhou, China. “Charlie has created the first believable model of the impact of pricing on transportation choices,” says Sam Schwartz, a former New York City traffic commissioner who actually coined the word gridlock.
It’s also the most ambitious effort yet to impose mathematical rigor and predictability on an inherently chaotic phenomenon. Despite decades of attempts to curb delays—adding lanes to highways, synchronizing traffic lights—planners haven’t had much success at unsnarling gridlock. A study by the Texas Transportation Institute found that in 2007, metropolitan-area drivers in the US spent an average of 36 hours stuck in traffic—up from 14 hours in 1982.
But the BTA, Komanoff says, will finally allow engineers to model the effects of proposed transportation policies in realistic detail. He translates all traffic impacts—delays, collisions, injuries, air pollution—into dollars and cents; that way, it’s easy for users to compare the benefits and costs of different plans. He has even come up with a plan of his own that would, according to his calculations, collect $1.3 billion in motorist tolls per year—all of which would be spent on improving public transit—and save $2.5 billion in time costs by reducing delays. To that, add $190 million from decreased mortality as a result of making streets more bicycle- and pedestrian-friendly, $83 million in collision damage reduction, and $34 million in lower CO2 emissions.
But there’s one aspect of Komanoff’s plan that his spreadsheet can’t help with: how to put it into practice. Americans hate the idea of paying to drive on public roads. No US city has succeeded at passing any plan remotely like Komanoff’s. And the response from New York City’s Department of Transportation has been tepid at best. Komanoff may have created a vision of the traffic system of the future, but he’s still stuck with the government and politics of the present.
Ebb and Flow:
A Day in the Life of Manhattan Traffic
Charles Komanoff has spent three years building a model of the traffic patterns in New York City. The result is an exhaustive accounting of every mile traveled, every slowdown encountered, and every hour wasted. Below, a rundown of traffic on an average weekday in Manhattan’s central business district.
Infographic: Pitch Interactive
Infographic: Pitch Interactive
Komanoff’s life has been driven by two passions: cycling and data. Naturally, he has combined them in another spreadsheet, one that logs every mile he has biked since January 1, 2001. The very act of entering the data, Komanoff says, keeps him motivated to ride everywhere, even in the rain and snow. “I want to be able to enter the miles,” he says. He ends up inputting about 3,000 of them every year.
A bearded former antiwar activist, Komanoff grew up in a liberal enclave of Long Island and studied mathematics and economics at Harvard. In 1973, he analyzed a proposed hydroelectric facility in upstate New York whose business model relied on the existence of extensive nuclear power in the Northeast. He wrote a report showing that the kilowatt price of nuclear power was rising fast and that the economics of the scheme simply didn’t work. It was his professional breakthrough, and in 1981 he published a massive book (.pdf) on the subject, Power Plant Cost Escalation: Nuclear and Coal Capital Costs, Regulation and Economics. “I thought I’d never do anything that ambitious again,” he says.
Over the next 30 years, Komanoff built a career at this intersection of algorithms and advocacy, especially around what he calls “the two leading sources of environmental and social harm in industrial societies: electricity generation and motor vehicles.”
As an energy analyst, Komanoff has published several books and reports and has consulted for dozens of US state and federal agencies. He started getting involved in transportation issues in 1986, when he resuscitated Transportation Alternatives, an advocacy organization that lobbies for policies that favor cycling, walking, and public transportation and which is now a major force in New York City politics. He also cofounded a pedestrian rights organization, Right of Way, in 1996. Two and a half years later, he produced a detailed statistical analysis of pedestrian and cyclist deaths—it showed that casualties are not random, unpredictable accidents but the foreseeable result of given traffic conditions.
Komanoff’s work may not have made him a celebrity, but his rigor gained him a reputation within the rarefied world of traffic geeks. In 2007, he got a phone call. Ted Kheel, a legendary labor lawyer and one of Komanoff’s heroes, had made it his personal mission to completely rethink New York City’s traffic policy. Was Komanoff free to help?
Now 95 years old, Kheel has been trying to improve New York’s traffic for more than half a century. He is obsessed with the economic damage that cars do to cities—damage that’s much greater than most people realize. In 1958, as the New York City Transit Authority was preparing to raise subway fares, Kheel wrote a paper citing a survey that found that traffic congestion cost more than $2 billion a year. “This vast sum,” Kheel wrote, “equal to $1 a working day for every man, woman, and child in the city, has to be paid by someone, and it is. It is assessed against all of us in the form of higher prices, inflated delivery costs, and increased taxes.” It would be cheaper, he argued, to subsidize public transportation and save the hidden costs associated with driving.
Kheel made the same point a decade later, in a New York magazine cover story arguing against another fare increase: “Any balanced analysis will surely prove that the taxpayer actually pays, for every person who chooses to drive to and from work in his own car, an indirect subsidy at least 10 times as great as the indirect subsidy now paid the mass-transit rider.”
The thread running through these essays is a concept familiar to all economists: the problem of negative externalities, costs that accrue when the self-interested actions of one person leave bystanders worse off. The biggest example of a negative externality is global warming: When we burn carbon-based fuels, we benefit ourselves while imposing a great cost on billions of other present and future inhabitants of the planet.
Urban planners know this problem all too well. After all, traffic is filled with negative externalities. A small action by one driver—a mere tap on the brakes—can have ripple effects that impact thousands of other motorists. But because externalities are so hard to calculate, and because the costs are not paid out of any central budget, planners had always struggled to incorporate them in their analysis—which typically meant that such costs were undercounted, if they were counted at all.
In 2007, Kheel was still advocating for a traffic plan that took externalities into account and offered free public transportation as a way to reduce them. His basic notion was to impose a “congestion fee” on any driver entering New York’s central business district—the area south of 60th Street—and use the proceeds to pay for everything from subways and buses to improved pedestrian access.
But how much to charge? Kheel could make only an educated guess. Then he found Komanoff, a man who shared his goals and had the mathematical chops to help realize them. Drawing on his own personal savings and the resources of one of his foundations, Kheel offered to pay him to determine the optimal congestion fee.
Komanoff is the kind of guy who takes a little while to get focused on a subject—but once focused can carry on more or less indefinitely. That’s exactly what happened with the spreadsheet he created for Kheel. It turned out to be relatively straightforward to calculate a congestion charge that would pay for public transit; Komanoff arrived at a fee of $16 for every vehicle trip into the central business district. But he knew that he could come up with a model that was much more sophisticated. “I gave them what they were looking for,” Komanoff says. “And then I kept on asking myself more questions.”
So, after the report was released in January 2008, Komanoff requested more funding from Kheel to keep plugging away at the spreadsheet. One of the first tasks was to nail down those externalities. That meant figuring out exactly how much New Yorkers’ time was worth and how much of it they wasted in traffic. He started with a Brookings Institution estimate of the value of a US airline passenger’s time—about $53 an hour. Based on salary data from the Bureau of Labor Statistics, Komanoff bumped that up by 20 percent for people in New York City. He wanted to use conservative estimates, so he assumed that a car driver’s commuting time was 25 percent less valuable than an airline passenger’s; if someone was driving for nonwork purposes, their time was 50 percent less valuable. He drew on survey data to peg a taxi passenger’s time at 90 percent of the average air passenger’s; additional passengers—perhaps children—would be worth much less. Eventually, after taking into account the mix of cars, trucks, taxis, and buses in traffic—as well as the number of people in each type of vehicle—Komanoff concluded that the average vehicle in the central business district has a time value of $53.39 per hour; outside the CBD that number falls to $34.44. (Komanoff based some assumptions on his own research, but the spreadsheet allows anyone to plug in their own estimates to see how they affect the results.)
The rest of his calculations are more complicated. To work out the total delay caused by each car, Komanoff turned to a formula devised by UC Irvine economist Ken Small: S = 24.2/[1 + 0.1(V/Vk)4.08], where S is traffic speed, V is number of vehicles, and Vk is a constant that changes from city to city (it was originally set at an arbitrary level of 1,000 for an area of Toronto in 1978). For S and V, Komanoff drew on the city’s estimates of average daytime traffic speeds (8 mph) and volume (870,301 vehicles) within the CBD. This let him calculate the value of Vk, which came out to be 97,105. He then used that value of Vk and his own estimates of traffic volume to come up with a new—and, by his lights, more accurate—value for S. He then ran the equation again to find the value of S when 1,000 cars were added. The difference, divided by 1,000, represented the impact of each individual car.
In the end, Komanoff found that every car entering the CBD causes an average of 3.23 person-hours of delays. Multiply that by $39.53—a weighted average of vehicles’ time value within and outside the CBD—and it turns out that the average weekday vehicle journey costs other New Yorkers $128 in lost time. At last, urban planners could say just how big the externalities associated with driving are, knowing that the number was backed up with solid empirical analysis.
“The work Komanoff is doing will be essential,” says Tom Vanderbilt, author of Traffic: Why We Drive the Way We Do (and What It Says About Us). “He’s showing the impact of traffic in easy-to-understand language, considering all transport options, and getting away from the idea that transportation happens in a vacuum.”
Kheel hoped that Komanoff’s work would support a plan to offer completely free public transit. But Komanoff found that the system would still be overloaded at rush hour. Drivers had to be encouraged to travel at different times of the day. So he devised a new plan, one that charged both drivers and transit riders different rates at different times. It would charge $3 to cars entering the CBD on weekday nights, $6 for most of the day, and $9 during rush hour. The subway fare also varies, but is always less than the $2.25 it is today: $1 at night, rising to $1.50 as day breaks, and peaking at $2 during weekday rush hours. Buses are always free, because the time saved when passengers aren’t fumbling for change more than makes up for the lost fare revenue. Komanoff’s plan also imposes a 33 percent surcharge on every taxi ride, 10 percent of which would go to the cab driver and the rest to the city.
Komanoff’s plan is vastly more sophisticated than a simple bridge toll. Instead of merely punishing drivers, he has built a delicate system of incentives and revenue streams. Just as a musical fugue weaves several melodic lines into a complex yet harmonious whole, Komanoff’s policy assembles all the various modes of transportation into a coherent, integrated traffic system.
Komanoff’s plan may be ambitious. It may be mathematically correct. But it is unlikely ever to be adopted in the US. Cities like Stockholm and London have implemented so-called congestion pricing plans—systems that charge drivers different rates at different times—but Americans see street tolls as a new tax, and one that benefits relatively affluent city dwellers at the expense of hard-pressed suburban commuters. And the plan would require new toll plazas or license-plate-monitoring cameras, which many see as an invasion of privacy. (In 2008, a congestion-pricing plan proposed by New York mayor Michael Bloomberg was soundly rejected by the state legislature.)
But Komanoff’s followers can’t help but root for him. “This really could happen,” insists conservative analyst Reihan Salam, a longtime advocate of congestion pricing. Salam points out that Bloomberg’s plan was seen as pure punishment. Komanoff’s proposal would balance the fees with real benefits for New York’s subway and bus riders. “This makes New York more livable,” Salam says.
Still, for all of its sophistication, Komanoff’s plan remains imperfect. Komanoff himself admits that an ideal system would track drivers wherever they went, charging by the mile and the minute, with rates determined by location. He calls this “the holy grail of congestion pricing.”
Someday, technology will probably help fulfill this promise. Skymeter, a Toronto-based company, has developed a GPS-based metering system that can track and bill cars in even the densest urban areas. With such a system, Komanoff says, he could adjust congestion prices on a block-by-block basis. Cities could do away with parking meters and simply track how long cars sat at a curb. Insurance premiums could reflect the habits of individual drivers instead of relying on crude proxies like age. Drivers could be rewarded for taking the roads less traveled—not having to pay, and sometimes even getting paid, if they chose to commute on less congested routes on particularly busy days. “It’s going to happen,” Komanoff says. “Cities will charge per mile or per minute according to your exact location and the type of vehicle you’re driving.”
When it happens, Kheel and Komanoff will be lauded for their efforts to give empirical rigor to the fight to decongest cities. The only question is whether it will happen in Kheel’s lifetime—or, for that matter, in Komanoff’s.