Traffic (19 page)

Some of the start-up lost time could be “found” if drivers approached at a slower, more uniform speed that did not require them to come to a stop. (If they came
too
slowly, however, time would also be lost, as green signal time would be wasted on an empty intersection.) Much of the time being lost these days is “clearance lost time,” the time between signals when the intersection is momentarily empty. This is because traffic engineers are increasingly lengthening the “all-red phase,” meaning that when one direction gets the red, the competing direction has to wait nearly two seconds before getting a green. They do this because more people cannot seem to stop on red.

Now picture a highway during stop-and-go traffic. Like those drivers stopped at the light, each time we stop and start in a jam we are generating lost time. Unsure of what the drivers ahead are doing, we move in an unsteady way. We are distracted for a moment and do not accelerate. Or we overreact to brake lights, stopping harder than we need to and losing more time. Drivers talking on cell phones may lose still more time through delayed reactions and slower speeds. The closer the vehicles are packed together, the more they affect one another. Everything becomes more unstable. “All of the excess ability for the system to take in any sort of disturbance is gone,” says Coifman. He uses the metaphor of five croquet balls. “If you put them a foot apart and tap one lightly, nothing happens to the other four. If you put them all up against one another and tap one lightly, the far one then moves out. When you get closer to capacity on the roadway, if there’s any one little tweak, it impacts a lot of the cars.”

When the first in a group of closely spaced cars slows or stops, a “shock wave” is triggered that moves backward. The first car slows or stops, and the next one slows or stops a little farther back. This wave, whose speed usually seems to register at about 12 miles per hour, could theoretically go on for as long as there was a string of sufficiently dense traffic. Even a single car on a two-lane highway, by simply changing its speed with little rhyme or reason (as people so often seem to do, in what I like to call “speed-attention-deficit disorder”), can itself pump these waves back down a stream of following vehicles. Furthermore, even if that car’s average speed is fairly high, the fluctuations wreak progressive havoc. This was the secret behind the Holland Tunnel experiment: With cars limited to “platoons” of forty-four vehicles each, the shock waves that were triggered were confined to each group. The platoons were like croquet balls spaced apart.

Many times we find ourselves stuck in traffic that seems to have no visible cause. Or we make it through a jam and begin to speed up, seeming to make progress, only to quickly drive into another jam. “Phantom jams,” these have been called, to the annoyance of some. “Phantom jams are in reality nonexistent,” thunders Michael Schreckenberg, a German physics professor at the University of Duisburg-Essen so noted for his traffic studies that he has acquired the epithet “jam professor” in the German media. There is always a reason for a jam, he says, even if it is not apparent. What seems to be a local disturbance might just be a wave pumped up from downstream in what is in reality a big, wide moving jam. It is wrong, says Schreckenberg, to simply call the whole thing stop-and-go traffic: “Stop-and-go is the dynamic
within
a jam.”

We fall for the phantom-jam illusion because traffic happens in both time and space. You may be driving into a space where a jam has been. Or you may not be driving into a jam—instead, the jam might be driving into you. “In my bucket analogy,” says Coifman, “the driver would be a water molecule. If the water level’s rising, then the jam’s coming to us.” We are also driving into history—or, perhaps more accurately, we are being driven back into history. By the time we actually arrive where something triggered the shock wave, in all likelihood the event will be only a memory. It may have been an accident, now cleared. “The queue’s going to persist for a while as it’s dissipating,” says Coifman. “It’s that water sitting in the bucket. In this case you’ve enlarged the hole in the bucket, but it does not disappear instantaneously.”

Or the hiccup in heavy traffic that passes through you might be the echo of someone who, forward in space and backward in time, did something as simple as change lanes. The car that changes lanes moves, eating up capacity in the new lane and causing the driver behind to slow; it also frees up capacity in the lane it has left, which triggers a bit of acceleration in that lane. These actions ripple backward in a kind of seesaw effect. This is why, if you pick one car in the neighboring lane as your benchmark, you will often find yourself passing that car and being passed by that car continuously. This is equilibrium asserting itself, the accordion of traffic flow stretching and compressing, the lingering chain reaction of everyone who thought they could get a better deal.

Since it takes so long for traffic to resume flowing freely once it has plunged past the critical density, it would seem the best way to avoid the ill effects of a jam would be not to drive into it, or let it drive into you, in the first place. This is the thought that occurred one afternoon a few years ago to Bill Beatty, a self-described “amateur traffic physicist” who works in the physics laboratory at the University of Washington. Beatty was on State Highway 202, returning from a state fair. The road, a “little four-lane,” was thronged with traffic from the fair. The traffic was “completely periodic,” as he describes it. “You’d drive real fast and then almost get to sixty and then you’d slow down and come to a stop, for almost two minutes,” he says.

So Beatty decided to try an experiment: He would drive only 35 miles per hour. Rather than let the waves drive into him, he would “eat the waves,” or subdue the wildly varying oscillations of stop-and-go traffic. Instead of tailgating and constantly braking, he would try to drive at a uniform speed, leaving a large gap between himself and the car ahead. When he looked in his rearview mirror, he saw a revelation in the pattern of headlights: Those behind him looked to be in a regular pattern, while the other lane had clusters of clumped stop-and-go vehicles. He had “damped” the wave, leveled off the extremes. “It cuts off the mountains and puts them in the valley,” he says of his technique. “So instead of getting to drive at sixty miles per hour briefly, you’re forced to drive at thirty-five miles per hour. But you don’t have to stop, either.”

Without analyzing the total traffic flow of the highway, it would be hard to know for sure what good Beatty’s experiment did. People may have just merged in front of him, pushing him back (if he wanted to keep the same following distance), while those behind him who thought he was going too slow may have jumped into the next lane, causing additional disturbance. But even if Beatty’s technique did little more than take a tightly congested traffic jam and stretch it backward, so that a car spent the same amount of time traveling a section of road, it would still save fuel and reduce the risk of rear-end accidents—two added benefits for the same price. Only how do you get everyone to cooperate? How do you prevent people, as so often seems to happen, from simply consuming the space you have left open? How, in essence, can we simulate ant-trail behavior on the highway?

One way is the “variable speed limit” system now being used on any number of roads, from England’s M25 “controlled motorway” to sections of the German autobahn to the Western Ring Road in Melbourne, Australia. These systems link loop detectors in the road to changeable speed-limit signs. When the system notices that traffic has slowed, it sends an alert upstream. The approaching drivers are given a mandatory speed limit (enforced by license-plate cameras) that should, in theory, lessen the effects of a shock wave. Even though many drivers suspected it was the lowering of speeds to 40 kilometers per hour that was
causing
the congestion, a study of the M25 found that drivers spent less time in stop-and-go traffic, which not only helped lower the crash rate by 20 percent (itself good for traffic flow) but cut vehicle emissions by nearly 10 percent. As drivers adjusted to the system, their trip times declined. Again, slower can be faster.

Smart highways also require smart drivers. The sad truth is that the way we drive is responsible for a good part of our traffic problems. We accelerate too slowly or brake too quickly, or the opposite; since we do not leave enough space between vehicles, the effects are often magnified as they move back up the line. Traffic is what is known as a nonlinear system, meaning most simply a system whose output cannot be reliably predicted from its input. When the first car in a long platoon comes to a stop, one cannot exactly predict how quickly or how far back each car behind it will stop (if they come to a stop at all). And the farther back, the harder it is to predict.

A driver’s overreaction (or underreaction) may amplify a shock wave that snaps, like the crack of a whip, several cars back, helping to cause a collision in the space that the originating driver has since left. One study examined a crash on a Minneapolis highway involving a platoon of seven vehicles that had been forced to come to a sudden stop. The seventh car in the group crashed into the sixth. Since we normally assume that cars keeping an adequate following distance should be able to stop in all conditions, that should be the end of it.

But the researchers, examining the braking trajectories of the vehicles in the platoon, found that the
third
car arguably bore a considerable responsibility for the crash. How so? Because the third car was overly slow to react, it “consumed” a larger portion of the “shared resource” of braking distance allocated among the cars. This left the cars farther down the line with progressively less time and space in which to stop—to the point where the seventh car, even though it reacted faster than the third, was following too closely to the sixth car to stop under the amplified conditions. Had the third car’s reaction been faster, the crash might have been prevented. For these sorts of reasons, the researchers pointed out, people who tailgate—that is, do not follow at the “socially optimal” distance—increase their risk not only of striking the vehicle they’re following but of being struck
by the car following them.

What if drivers’ reaction times could be predicted with mathematical precision? The ultimate answer may be to combine smart highways with smart cars. It’s probably no accident that whenever one hears of a smart technology, it refers to something that has been taken out of human control. L. Craig Davis, a retired physicist who worked for many years in the research laboratories of the Ford Motor Company, is one of a number of people who have run simulations showing how equipping cars with adaptive cruise control (ACC), already found on many high-end models, can improve traffic flow by keeping the distance between cars at varying speeds mathematically perfect. This would not kill traffic waves entirely, says Davis. Even if a line of stopped cars could be coordinated to begin accelerating at the same time, he says, “if you wanted to get them up to speed with a normal distance between them at sixty miles per hour, you would still have this wave effect.”

Remarkably, the simulations show that if just one in ten drivers had ACC, a jam could be made much less worse; with as few as two in ten drivers, the jam
could be avoided altogether.
In one experiment, Davis located the precise moment the jam was avoided, just as one additional manual car was given ACC. This putative straw that broke the camel’s back brings to mind the example of the locusts. When the locusts reached critical density—one more locust—they began to behave entirely differently.

Just one problem has arisen in Davis’s simulations. Since the simulated vehicles with ACC like to keep very tight gaps between themselves, it may be difficult for a non-ACC car entering from an on-ramp to find a safe space between them. Also, like human drivers, ACC cars may not feel obliged to yield to entering drivers. These problems can surely be solved scientifically, but in the meantime, as we suffer the effects of our failure to always act cooperatively on the highway, we can draw one comforting lesson: Even machines sometimes have trouble merging.

Why Women Cause More Congestion Than Men (and Other Secrets of Traffic)

You’re not stuck in a traffic jam. You are the traffic jam.

—advertisement in Germany

One of the curious laws of traffic is that most people, the world over, spend roughly the same amount of time each day getting to where they need to go. Whether the setting is an African village or an American city, the daily round-trip commute clocks in at about 1.1 hours.

In the 1970s, Yacov Zahavi, an Israeli economist working for the World Bank, introduced a theory he called the “travel-time budget.” He suggested that people were willing to devote a certain part of each day to moving around. Interestingly, Zahavi found that this time was “practically the same” in all kinds of different locations. The small English city of Kingston-upon-Hull’s physical area was only 4.4 percent the size of London; nevertheless, Zahavi found, car drivers in both places averaged three-quarters of an hour each day. The only difference was that London drivers made fewer, longer trips, while Kingston-upon-Hull drivers made more frequent, shorter trips. In any case, the time spent driving was about the same.

The noted Italian physicist Cesare Marchetti has taken this idea one step further and pointed out that throughout history, well before the car, humans have sought to keep their commute at about one hour. This “cave instinct,” as he calls it, reflects a balance between our desires for mobility (the more territory, the more resources one can acquire, the more mates one can meet, etc.) and domesticity (we tend to feel safer and more comfortable at home than on the road). Even prisoners with life sentences, he notes, get an hour “out in the yard.” When walking was our only commuting option, an average walking speed of 5 kilometers per hour meant that the daily commute to and from the cave would allow one to cover an area of roughly 7 square miles (or 20 square kilometers). This, remarks Marchetti, is
exactly
the mean area of Greek villages to this day. Moreover, Marchetti notes, none of the ancient city walls, from Rome to Persepolis, encompassed a space wider than 5 kilometers in diameter—in other words, just the right size so that one could walk from the edge of town to the center and back in one hour. Today, the old core of a pedestrian city like Venice still has a diameter of 5 kilometers.

The growth of cities was marked, like tree rings, by advances in the ways we had to get from one place to another. The Berlin of 1800, Marchetti points out, was a walkable size. But as horse trams came along, then electric trams, then subways, and, finally, the car, the city kept growing, by roughly an amount proportional to the speed increase of the new commuting technology—but always such that the center of the city was, roughly, thirty minutes away for most people.

The “one-hour rule” found in ancient Rome still exists in modern America (and most other places), even if we have swapped sandals for cars or subways. “The thing to recognize is that half the U.S. population still gets to work in almost twenty minutes, or under twenty minutes,” says Alan Pisarski, the country’s leading authority in the field of “travel behavior.” For decades, Pisarski has been compiling numbers for the U.S. Census on how we get to work and how long that trip takes us. There seems to be some innate human limit for travel—which makes sense, after all, if one sleeps eight hours, works eight hours, spends a few hours eating (and not in the car), and crams in a hobby or a child’s tap-dance recital. Not much time is left. Studies have shown that satisfaction with one’s commute begins to drop off at around thirty minutes each way.

The enduring persistence of the one-hour rule was shown in a paper by urban planning researchers David Levinson and Ajay Kumar. Looking at the Washington, D.C., metropolitan area over a number of years from the 1950s to the 1980s, they found that average travel times—around thirty-two minutes each way—had hardly budged across the decades. What
had
changed were two other factors: distance and average travel speed. Both had gone up. They suggested that people were acting as “rational locators.” Because they did not want to spend too long commuting, they had moved to more distant suburbs. They had longer distances to drive, but they could now travel on faster suburban roads, rather than crowded city streets, to get to where their jobs were located. (Those in the center city, meanwhile, were probably walking to work or taking the Metro, meaning their times had hardly changed as well.)

“Wait,” I can hear you say, “I thought traffic was getting worse.” For many people, it undoubtedly is. The Texas Transportation Institute estimates that total traffic delay in the United States went from 0.7 billion hours in 1982 to 3.7 billion hours in 2003. In the twenty-six largest urban areas, the delay grew almost 655 percent in those same years. The U.S. Census noted that in most large cities, it took longer to get to work in 2000 than it did in 1990. The authors of the “rational locator” study took another look at the issue and decided that perhaps travel times were
not
stable after all. Perhaps, they suggested, it was a “statistical artifact.” Cities were growing larger every year, gobbling up new counties into their “metropolitan region,” so maybe more-distant drivers who were not tallied in previous surveys were now being captured, jacking up the numbers. Or maybe the suburbs that they had moved to previously to escape congestion were now themselves getting congested. Perhaps the total outcome of all that rational location had itself become irrational.

But why exactly is it getting worse? Or, to ask a question I sometimes do when I encounter unexpectedly heavy congestion in the middle of the day, “Who are all these people?” There are obvious answers, the ones you yourself suspect, like the fact that we add new drivers faster than we keep adding new blacktop. To take a quite typical American example: In suburban Montgomery County, Maryland, just outside Washington, D.C., the population grew by some 7 percent between 1976 and 1985. The number of jobs grew too, by 20 percent. But vehicle registrations nearly doubled. The county, which hardly built any new roads at all during that period, was suddenly awash in cars. Studies show that when a household has more vehicles, it not only drives more as a total household, as one would expect, but
each person
puts on more miles, almost as if the presence of those extra vehicles prompts more driving.

Affluence breeds traffic. Or, as Alan Pisarski describes it, congestion is “people with the economic means to act on their social and economic interests getting in the way of other people with the means to act on theirs.” The more money people have, the more cars they own, the more they drive (with the exception of a few Manhattan millionaires). The better the economy, the more miles traveled, the worse the traffic congestion. This is the interesting thing about studying traffic behavior: It reveals what Pisarski terms our “lines of desire.” The U.S. Census is like a staid group portrait of the country. It shows us all in our homes, with our 2.3 bathrooms and 1.3 cats. But it does not really show us how we got there. The travel census is like a frantic, blurred snapshot of a nation in motion. It catches us on the move, in an unrehearsed moment, busily going about our daily lives in order to afford that house with 2.3 bathrooms. It may tell us more about ourselves than we know.

One striking thing the numbers seem to reveal is that women now make the largest contribution to congestion. (Another way to look at this is that they also suffer from it the most.) This seems like a controversial statement, and indeed one like it got a highway official booed at a conference. The statistic doesn’t assign fault or suggest that women working is a bad thing; it does provide a fascinating example of how traffic patterns are not just anonymous flows in the models of engineers, but moving, breathing time lines of social change.

Many of us can remember or envision a time when the typical commute involved Dad driving to the office while Mom took care of the kids and ran errands around town. Or, because many American families had only one car, Dad was driven to the morning train and picked up again just in time for cocktail hour and Cronkite. This is a blinkered view, argues Sandra Rosenbloom, an urban planning professor at Arizona State University whose specialty is women’s travel behavior. “That was just a middle-class model,” she says. “Lower-class women always worked. Either alongside husbands in stores, or at home doing piecework. Women always worked.”

Still, the
Leave It to Beaver
commute was not a total fiction, given that in 1950 women made up 28 percent of the workforce. Today, that figure is 48 percent. How could the roads
not
have gotten more crowded? “The rise in the number of cars, driver’s licenses, miles traveled—it totally tracks women going into the labor force,” says Rosenbloom. “It’s not that men wouldn’t have driven more, but you wouldn’t see these astonishing increases in traffic congestion in all indices of travel if women weren’t in the labor force, driving.”

The rise in working women is only part of the story. After all, they still represent a minority of the workforce, and studies show that men still rack up more miles when they drive to work. But work is an increasingly small part of the picture. In the 1950s, studies revealed that about 40 percent of daily trips per capita were “work trips.” Now the nationwide figure is roughly 16 percent. It’s not that people are making fewer trips to work but that they’re making so many other kinds of trips. What kinds of trips? Taking the kids to school or day care or soccer practice, eating out, picking up dry cleaning. In 1960, the average American drove 20.64 miles a day. By 2001, that figure was over 32 miles.

Who’s making these trips? Mostly women. This is the kind of social reality that traffic patterns lay on the table: Even though women make up nearly half the workforce, and their commutes are growing increasingly close in time and distance to men’s, they’re still doing a larger share of the household activities that, back in the
Leave It to Beaver
days, they may have had the whole day to complete (and, as Rosenbloom points out, 85 percent of single parents are women). “If you look at trip rates by male versus female, and look at that by size of family,” Pisarski says, “the women’s trip rates vary tremendously by size of family. Men’s trip rates look as if they didn’t even know they
had
a family. The men’s trip rates are almost independent of family size. What it obviously says is that the mother’s the one doing all the hauling.”

In fact, women make roughly double the number of what are called “serve-passenger” trips—that is, they’re taking someone somewhere that they themselves do not need to be. All these trips are squeezed together to and from work in a process called “trip chaining.” And because women, as a whole, leave later for work than men, they tend to travel right smack-dab in the peak hours of congestion (and even more so in the afternoon peak hours, which is partially why those tend to be worse). What’s more, these kinds of trips are made on the kinds of local streets, with lots of signals and required turning movements, that are least equipped to handle heavy traffic flows.

Another way trip chaining has helped increase traffic congestion is that it has made carpooling virtually impossible. Who wants to share a ride with someone who is going to day care, picking up laundry, dropping by Blockbuster, stopping at Aunt Clarice’s (“but just for a second”)? Carpooling keeps dropping in the United States (save among some immigrant groups), but “fam-pools,” car pools made up of family members (and almost 100 percent of fam-pools are
only
family members), keep rising. An estimated 83 percent of car pools are now fam-pools.

This raises the question of whether car-pool lanes are a good idea that has gone bad. If most people “carpooling” are simply toting their families around, taking no additional cars off the road and statistically driving more miles (thus creating more traffic), why should they get a break on the highway? Is a policy meant to reduce the number of drivers just acting as a “mommy lane,” enabling drivers with children to do their trip chaining more quickly and thus encouraging more of it? (Some pregnant women have taken this to extremes, arguing that their unborn children are precocious car poolers).

That women suffer more from congestion, even if at the hands of other women, is demonstrated in the high-occupancy toll lanes (HOT lanes, a.k.a. Lexus lanes) in cities like Denver, where drivers pay more to travel on less congested roads. Rosenbloom notes that studies show that women pay to use the lanes more often than men do—despite making less money on average. “And they are not just high-income women,” she says. “Even if you don’t make very much money, you’ve got to get your kids from day care. Every minute they stay over, they penalize you. Or these women have second jobs they have to get to on time.”

Women are not to be
blamed
for congestion, Rosenbloom argues. “The fault is the way families live today. The car is the way the two-worker families balance all the things they have to do.” Where children might once have been cared for at home, they are now shuttled to day care. Where it was once the overwhelming norm for children to walk to school, today only about 15 percent do. Parents on the “school run” are thought to boost traffic on the roads by some 30 percent.