venerdì 17 marzo 2017

Traffic by Tom Vanderbilt

Traffic by Tom Vanderbilt
You have 208 highlighted passages
You have 167 notes
Last annotated on March 17, 2017
Chapter One Why Does the Other Lane Always Seem Faster? How Traffic Messes with Our HeadsRead more at location 351
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Shut Up, I Can’t Hear You: Anonymity, Aggression, and the Problems of Communicating While DrivingRead more at location 353
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HORN BROKEN. WATCH FOR FINGER. —bumper stickerRead more at location 354
Are You Lookin’ at Me? Eye Contact, Stereotypes, and Social Interaction on the RoadRead more at location 521
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Jay Phelan, an evolutionary biologist who works a few buildings over from Jack Katz at UCLA, often thinks about traffic as he pilots his motorcycle through Los Angeles. “We evolved in a world in which there were about a hundred people in the group you were in,” he says. “Every person you saw you had an ongoing relationship with.” Was that person good to you? Did they return the spear they borrowed last week? This way of getting along is called “reciprocal altruism.” You scratch my back, I’ll scratch yours; we each do it because we think it will benefit us “down the road.” What happens in traffic, Phelan explains, is that even though we may be driving around Los Angeles with hundreds of thousands of anonymous others, in our ancient brains we are Fred Flintstones (albeit not driving with our feet), still inhabiting our little prehistoric village. “So when someone does something nice for you on the road, you’re processing it like, ‘Wow, I’ve got an ally now.’ The brain encodes it as the beginning of a long-term reciprocal relationship.”Read more at location 531
This sense of fairness might cause us to do things in traffic like aggressively tailgate someone who has done the same to us. We do this despite the costs to our own safety (we might crash, they might be homicidal) and the fact that we will never see the person we are punishing again.Read more at location 552
The Swiss economist Ernst Fehr and his colleagues have proposed a theory of “strong reciprocity,”36 which they define as “a willingness to sacrifice resources for rewarding fair and punishing unfair behavior even if this is costly and provides neither present nor future material rewards for the reciprocator.”Read more at location 560
So perhaps, as the economist Herbert Gintis suggests, certain forms of supposed “road rage” are good things.Read more at location 568
Because eye contact is so absent in traffic, it can feel uncomfortable when it does happen. Have you ever been stopped at a light and “felt” someone in a neighboring car looking at you? It probably made you uneasy. The first reason for this is that it may violate the sense of privacy we feel in traffic.Read more at location 581
When you need to do something like change lanes, however, eye contact is a key traffic signal.Read more at location 590
Many studies have confirmed this: Eye contact greatly increases the chances of gaining cooperation in various experimental games (it worked for Seinfeld’s George, by the way). Curiously, the eyes do not even need to be real. One study showed that the presence of cartoon eyes on a computer screen made people give more money to another unseen player than when the eyes were not present.40 In another study, researchers put photographs of eyes above an “honor system” coffee machine in a university break room.41Read more at location 593
Waiting in Line, Waiting in Traffic: Why the Other Lane Always Moves FasterRead more at location 761
waits.” Think of ramp meters, those signals that delay drivers’ entrance onto the freeway. Drivers fume: Why should I have to wait on the ramp while the freeway is moving? One study found that people thought of waiting on the ramp as 1.6 to 1.7 times “more onerous” than waiting on the highway itself.68 The more people understand the purpose of ramp meters (which I will discuss in Chapter 4), the less bothersome the wait becomes. This relates to proposition no. 5: “Unexplained waits are longer than explained waits.” Hence our frustration when we find no “cause” for a traffic jam. If we know there is an accident or construction, the delay is easier to process. Proposition no. 8 is appropriate, too: “Solo waiting feels longer than group waiting.”Read more at location 790
Chapter Two Why You’re Not as Good a Driver as You Think You AreRead more at location 972
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If Driving Is So Easy, Why Is It So Hard for a Robot? What Teaching Machines to Drive Teaches Us About DrivingRead more at location 973
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For those of us who aren’t brain surgeons, driving is probably the most complex everyday thing we do.Read more at location 977
Engineers call the moment when we’re too close to the amber light to stop and yet too far to make it through without catching some of the red phase the “dilemma zone.” And a dilemma it is.Read more at location 1036
In traffic, these sorts of dilemma zones occur all the time.Read more at location 1049
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How’s My Driving? How the Hell Should I Know? Why Lack of Feedback Fails Us on the RoadRead more at location 1091
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What if there was an eBay-like system of “reputation management” for traffic? This idea was raised in a provocative paper by Lior J. Strahilevitz,Read more at location 1107
Less ambitious and official versions of this have been tried.16 The Web site, which was begun, in the words of its founder, “to make people more accountable for their actions on the roadways in one forum or another,” gives drivers a place to lodge complaints about bad drivers, along with the offenders’ license plate numbers; posts chastise “Too Busy Brushing Her Hair” in California and “Audi A-hole” in New Jersey. Much less frequently, users give kudos to good drivers.Read more at location 1126
Monty Python: “We Are All Above Average!” Psychologists have called this phenomenon “optimistic bias” (or the “above-average effect”), and it is still something of a mystery why we do it. It might be that we want to make ourselves out to be better than others in a kind of downward comparison, the way the people in line in the first chapter assessed their own well-being by turning around to look at those lesser beings at the back of the queue. Or it might be the psychic crutch we need to more confidently face driving, the most dangerous thing19 most of us will ever do.Read more at location 1143
Chapter Three How Our Eyes and Minds Betray Us on the RoadRead more at location 1401
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Keep Your Mind on the Road: Why It’s So Hard to Pay Attention in TrafficRead more at location 1403
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You realize, with a mixture of wonder and horror, that you cannot remember what you have been doing for the past few moments—nor do you know how long you have been “out.”Read more at location 1407
“How did I get here?”Read more at location 1409
“highway hypnosis”Read more at location 1410
“time-gap experience,Read more at location 1410
What is also unclear is how much attention we were actually paying to the road while under the spell of highway hypnosisRead more at location 1413
Why is it so hard to pay attention while we are driving?Read more at location 1420
Driving, for most of us, is what psychologists call an “overlearned” activity. It is something we’re so well practiced at that we’re able to do it without much conscious thought.Read more at location 1421
the better we become at it, the less we think of each individual step.Read more at location 1424
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The more overlearned an activity becomes, the less cognitive workload it imposes—Read more at location 1430
Too little workload has its own problems. We get bored. We get tired. We lapse into highway hypnosis. We may make errors.Read more at location 1438
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Most driving rarely requires our full workload. So we listen to the radio, look out the window, or, increasingly, talk on the cell phone or read text messages—in the case of one fatal crash in California, the driver may have been operating a laptop computer as he drove.Read more at location 1443
This raises another point: Researchers look at how driving is affected when people do other things, but research also shows that secondary tasks suffer as well. We become worse drivers and worse talkers.Read more at location 1454
It’s like speed-reading. You think you can read really fast but your comprehension disappears.Read more at location 1459
we buy into the myth of multitasking with little actual knowledge of how much we can really add in or, as with the television news, how much we are missing.Read more at location 1464
The sources of distraction inside a car have been painstakingly logged by researchers. We know that the average driver adjusts their radio 7.4 times per hour of driving, that their attention is diverted 8.1 times per hour by infants, and that they search for something—sunglasses, breath mints, change for the toll—10.8 times per hour.8 Research has further revealed just how many times we glance off the road to do these things and how long each glance takes: In general, the average driver looks away from the road for .06 seconds9 every 3.4 seconds.Read more at location 1481
The drivers were redistributing workload. With more of their attention devoted to a cell phone conversation, they may have had to work just a bit harder to stay in their lane;Read more at location 1518
Something similar happens with very new drivers on highways: So much of their mental concentration is devoted to simply staying in the lane, they have trouble paying attention to their speed.Read more at location 1524
“If drivers are in an area that they already know, they almost don’t even see the sign, because they already know it’s there,” Andersen said.Read more at location 1556
Inattentional blindness, it has been suggested, is behind an entire category of crashes in traffic,Read more at location 1583
Objects in Traffic Are More Complicated Than They Appear: How Our Driving Eyes Deceive UsRead more at location 1706
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Try to picture, for a moment, the white stripes that divide the lanes on a major highway. How long would you guess they are? How much space would you say lies between each stripe? When first asked this question,Read more at location 1707
I use this as a simple example of how what we see is not always what we get as we move in the unnaturally high speeds of traffic.Read more at location 1713
As the naturalist Robert Winkler points out, creatures like hawks, whose eyes possess a much faster “flicker fusion rate” than humans’, can track small prey from high above as they dive at well over 100 miles per hour.50 The short answer is that we cheat.Read more at location 1715
Note: FALCHI Edit
What we see while driving is a visually impoverished view of the world.Read more at location 1720
you notice their bumper sticker: IF YOU CAN READ THIS, YOU’RE TOO CLOSE).Read more at location 1725
Traffic illusionsRead more at location 1729
the spokes on a car’s wheels sometimes seem to be moving “backward.” This so-called wagon-wheelRead more at location 1730
we perceive the world not as a continuous flow but in a series of discrete and sequential “frames.”Read more at location 1739
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in some places, engineers have tried to exploit this by employing “illusory pavement markings”54 to make drivers think they are going faster than they are.Read more at location 1760
These experiments have been focused on exit ramps because they are a statistically dangerous part of the highway.Read more at location 1766
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“speed adaptation.”Read more at location 1767
Have you ever noticed, when driving from a rural highway onto a village road with a lower speed limit, how absolutely slow it feels?Read more at location 1767
The longer we drive at high speeds, the harder it is for us to slow down.Read more at location 1769
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the “treadmill effect.”Read more at location 1773
Chapter Four Why Ants Don’t Get into Traffic Jams (and Humans Do): On Cooperation as a Cure for CongestionRead more at location 1940
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Meet the World’s Best Commuter: What We Can Learn from Ants, Locusts, and CricketsRead more at location 1941
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In both insect and human vehicular traffic, large patterns contain all kinds of hidden interactions. A subtle change in these interactions can dramatically affect the whole system.Read more at location 2001
the New World army ant, or Eciton burchellii, and these insects may just be the world’s best commuters. Army ant colonies are like mobile cities, boasting populations that can number over a million. Each dawn, the ants set out to earn their trade. The morning rush hour begins a bit groggily, but it quickly takes shape.Read more at location 2015
The secret to the ridiculous efficiency of army ant traffic is that, unlike traveling locusts—and humans—the ants are truly cooperative.Read more at location 2038
What about merging?Read more at location 2045
How are the ants at this difficult task?Read more at location 2046
That Oscar afternoon was a small but perfect illustration of how complicated human traffic is when compared to ant traffic.Read more at location 2107
Ants have evolved over countless centuries to move with a seamless synchronicity that will benefit the entire colony.Read more at location 2108
Los Angeles, like all cities, is essentially a noncooperative network.Read more at location 2113
Take traffic signals. It’s common to hear drivers in Los Angeles, as elsewhere, lament, “Why can’t they time the signals so they’re all green?” The obvious problem with so-called synchronized signals is that there is a driver moving in a different direction asking the same thing.Read more at location 2116
Engineers can use sophisticated models to squeeze as much “signal progression” as possible out of a network, to give the driver the “green wave.”Read more at location 2122
To further complicate matters, there are, even in Los Angeles, pedestrians.Read more at location 2135
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As a profession, traffic engineering has historically tended to treat pedestrians like little bits of irritating sand gumming up the works of their smoothly humming traffic machines.Read more at location 2137
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Engineers at Caltrans say that as a rule of thumb, for every one minute a highway lane is blocked, an additional four to five minutes of delay are generated.Read more at location 2183
the story is that there is no story,Read more at location 2191
He can tell which way a rainstorm is moving by looking at the real-time traffic-flow highway maps. He knows Fridays heading east out of the city can be particularly bad. “Everyone’s going to Las Vegas—all the way to ten p.m. that’ll be backed up.” He knows that people drive slower on highway stretches that have sound barriers to either side. He knows that mornings with heavy rains often lead to lighter afternoon traffic.Read more at location 2205
Note: IL MAGO Edit
When Slower Is Faster, or How the Few Defeat the Many: Traffic Flow and Human NatureRead more at location 2267
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ramp meters,Read more at location 2272
This is one of the most basic, and often overlooked, facts about traffic: That which is best for an individual’s interest may not be best for the common good.Read more at location 2275
Note: LEGGE Edit
The first efforts merely tried to model the process known as “car following.” This is based on the simple fact that the way you drive is affected by whether or not someone is in front of you, and how far away or close they are.Read more at location 2282
you’re influenced by the driver ahead,Read more at location 2284
Do you feel uncomfortable driving next to someone else, and therefore speed up or slow down? Are you sometimes willing, for no apparent reason, to ride quite close to the car in front, before gradually drifting back?Read more at location 2290
Note: CAR FOLLOWING - della serie non siamo formiche, ci spaventiamo troppo o troppo poco - l'attrito di chi non si tocca Edit
A study that looked into how closely passenger-car drivers followed SUVs found that car drivers, contrary to what they said they did—and despite the fact that the SUV was blocking their view of the traffic ahead—actually drove closer to SUVs than when they followed passenger cars.Read more at location 2293
Los Gatos effect,Read more at location 2295
You may have experienced this: Drivers seem reluctant to abandon the passing lane and join the lane of trucks chugging uphill, even when they are being pressured by other drivers, and even when the other lane is not crowded. What’s going on? Drivers may not want to give up the fast lane for fear of having trouble returning to it. They may also be unsure whether the person behind truly wants to go faster or is just keeping a tight space to prevent someone else from passing.Read more at location 2296
Note: CODE A SINISTRA - della serie non siamo formiche ma ingannati dall'istinto Edit
One of the idiosyncrasies I have noticed in traffic flow is something I call “passive-aggressive passing.” You’re in the passing lane when suddenly the driver behind you pressures you to move into the slower right-hand lane. After you have done so, they then move into your lane, in front of you, and slow down, thus forcing you to pass them.Read more at location 2300
Note: IL SORPASSO PASSIVO - non siamo formiche Edit
Ramp metering aims to keep the highway’s “main-line flow”Read more at location 2321
This means not only more cars but more cars jockeying to merge.Read more at location 2323
“That [merging] eventually breaks down the right lane,”Read more at location 2324
A line of cars waiting to exit an off-ramp can trigger this same chain reaction, one study showed, even when all the other lanes were flowing nowhere near critical density.Read more at location 2326
A simple way to see this in action involves rice. Take a liter of rice and pour it, all at once, through a funnel and into an empty beaker. Note how long it takes. Next, take the same rice and pour it not all at once but in a smooth, controlled flow, and time that process. Which liter of rice gets through more quickly?Read more at location 2330
Rice has more to do with traffic than you might think. Many people use water analogies when talking about traffic, because it’s a great way to describe concepts like volume and capacity.Read more at location 2335
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bottlenecks,Read more at location 2343
The inflow of rice exceeds the capacity of the funnel opening. The system gets denser and denser. Particles spend more time touching one another. More rice touches more rice.Read more at location 2350
Pouring less rice at a time—or moving fewer cars—keeps more space, and fewer interactions, between the grains.Read more at location 2354
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The “slower is faster” idea shows up often in traffic. The classic example concerns roundabouts.Read more at location 2362
Note: ROTONDE Edit
a properly designed roundabout can reduce delays by up to 65 percent over an intersection with traffic signals or stop signs. Sure, an individual driver who has a green light may fly through a signalized intersection much more quickly than through a roundabout. Roughly half the time, however, the light will not be green; and even if it is green there is often a rolling queue of vehicles just starting up from the previous red. Add to this such complications as left-turn arrows, which prevent the majority of drivers from moving, not to mention the “clearance phase,” that capacity-deadening moment when all lights must be red, to make sure everyone has cleared the intersection.Read more at location 2363
Note: c Edit
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The first cars in a queue squander an average of two seconds each, two seconds that would not have been lost had the car sailed through at the “saturation-flow” rate.Read more at location 2378
Chapter Five Why Women Cause More Congestion Than Men (and Other Secrets of Traffic)Read more at location 2482
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Who Are All These People? The Psychology of CommutingRead more at location 2483
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You’re not stuck in a traffic jam. You are the traffic jam. —advertisement in GermanyRead more at location 2484
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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.Read more at location 2486
Note: 1 ORA Edit
One striking thing the numbers seem to reveal is that women now make the largest contribution to congestion.Read more at location 2542
Many of us can remember or envision a time when the typical commute involved Dad driving to the office while Mom took careRead more at location 2546
American families had only one car,Read more at location 2547
in 1950 women made up 28 percent of the workforce. Today, that figure is 48 percent.Read more at location 2551
Note: OCCUPAZ Edit
you wouldn’t see these astonishing increases in traffic congestion in all indices of travel if women weren’t in the labor force, driving.”Read more at location 2554
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.10 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?Read more at location 2557
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.Read more at location 2559
The Parking Problem: Why We Are Inefficient Parkers and How This Causes CongestionRead more at location 2710
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The next time you find yourself at a shopping mall or a store with a large parking lot where the store entrance more or less divides the lot in half by width, take a moment to observe how the cars are arrayed. Unless the lot is completely filled, you may be able to observe a common pattern. Chances are, the row that is dead opposite the store entrance will be the most filled, with cars stretching far out along the row. In each adjacent row, there are likely to be slightly fewer cars. This pattern will continue sequentially in each row so that if one were able to gaze down at the lot from above (as anyone can with Google Earth), the cluster of cars might look, depending on the lot’s occupancy, like a giant Christmas tree or, perhaps, like a bell.Read more at location 2714
Whatever the case, something curious happens in parking lots. It seems that the people who actively look for the “best” parking place inevitably spend more total time getting to the store than those people who simply grab the first spot they see. This was the conclusion that Andrew Velkey, a psychology professor at Virginia’s Christopher Newport University, came to after he studied the behavior of parkers at a Wal-Mart in Mississippi.Read more at location 2725
Velkey wondered if a “gender effect” existed in the way women and men perceived distance and travel time (previous studies have arrived at mixed conclusions on this),51 So he gathered a group of subjects and had them estimate the distance to an object at varying locations, and then asked them to estimate the time it would take them to walk there. Men seemed to underestimate how long it would take to walk, while women seemed to overestimate it—which might explain the differences in parking strategies.Read more at location 2745
lot, Velkey saw two kinds of behavior emerge: an active and a passive search strategy. Some people would drive around the lot looking for a space, while others would sit at the head of a row and wait for someone to leave. In terms of the avian foraging models Velkey usually studied, the active searchers were like condors, soaring and looking for prey; the passive searchers, meanwhile, were like barn owls, perched and lying in wait.Read more at location 2756
In our daily lives as parkers, we face these foraging questions. We must decide whether to act like condors or barn owls.Read more at location 2779
But neither animals nor humans always follow optimal strategies. One reason is that not enough information might be available—Read more at location 2788
The Nobel Prize–winning economist Herbert Simon has suggested, in a seminal theory he called “satisficing” (a mix of satisfying and suffice), that because it is so hard for humans to always behave in the optimal way, we tend to make choices that leave us not with the “best” result but a result that is “good enough.”58 To take the bell-curve parking patterns described earlier as an example, drivers may have entered the lot with a general goal of getting the “best” spot, that is, in the row closest to the entrance. Once they were in the row, however, the goal changed to getting the best spot in that row.Read more at location 2796
What you may not realize, when you find yourself driving on a crowded city street, is that many of your fellow drivers on that crowded street are simply cruising for parking.Read more at location 2824
titled The High Cost of Free Parking.Read more at location 2827
Why More Roads Lead to More Traffic (and What to Do About It)Read more at location 2891
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The Selfish CommuterRead more at location 2892
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When a road is once built, it is a strange thing how it collects traffic. —Robert Louis StevensonRead more at location 2893
Note: STEVE Edit
“latent demand.Read more at location 2910
Engineers have a phrase: “It’ll be all right by Friday.”2 This rough rule of thumb means that even if on Monday something major happens that throws off the usual traffic patterns—a road is closed, a temporary detour set up—by the next Friday (or so) enough people should have reacted to the change in some way to bring the system back to something resembling normal.Read more at location 2915
Things are going to keep balancing.Read more at location 2919
The instant that this line is finished there will arise a demand for other lines.”Read more at location 2928
Do we build more roads because there are more people and more traffic, or does building those roads create a “special traffic all its own”?Read more at location 2930
Note: DILEMMA Edit
studies suggest that induced travel is real:Read more at location 2933
If you do not believe that new roads bring new drivers, consider what happens when roads are taken away.Read more at location 2940
Note: BLOCCHI Edit
“disappearing traffic,”Read more at location 2942
There is another way, a bit more subtle and complicated, that new roads can cause more traffic: the Braess paradox.Read more at location 2987
Note: BRAESS Edit
German mathematician, Dietrich Braess.Read more at location 2989
the paradox he discovered says that adding a new road to a transportation network, rather than making things better, may actually slow things down for all its users (even if, unlike in the “latent demand” example, no new drivers have been induced onto the roads).Read more at location 2989
First, imagine there are two roads running from one city to another. There is Sure Thing Street, a two-lane local street that always takes an hour. Then there is Take a Chance Highway, where the trip can be half an hour if it’s not crowded, but otherwise also takes an hour. Since most people feel lucky, they get on Take a Chance Highway—and end up spending an hour. From the point of view of the individual driver, this behavior makes sense.Read more at location 2995
Note: INTUITO Edit
If you cannot improve your situation, why move to a different road?Read more at location 3001
Note: c Edit
when everyone does what is best for him- or herself, they’re not doing what is best for everyone.Read more at location 3002
Note: c Edit
On the other hand, if a traffic cop stood at the junction of the two roads and directed half the drivers to Sure Thing Street and half to Take a Chance Highway, the drivers on Sure Thing Street would get home no sooner, but the highway drivers would get home twice as fast. Overall, the total travel time would drop.Read more at location 3003
Note: c Edit
imagine again the two hypothetical roads I mentioned, but this time imagine that halfway between the two cities, Take a Chance Highway (where the trip takes less than an hour by however many fewer drivers choose it) becomes like Sure Thing Street (always an hour), and vice versa.Read more at location 3006
Note: c Edit
But now imagine that a bridge is built connecting the two roads, right at the halfway point where Take a Chance becomes Sure Thing, and vice versa. Now drivers who began on Take a Chance Highway and found that it was not so good take the bridge to the other Take a Chance Highway segment. Meanwhile, drivers who began on Sure Thing Street are not about to cross the bridge and move to the other Sure Thing Street when, instead, they could stick around as their road becomes Take a Chance Highway (who knows, they might get lucky). The problem is that if everyone tries to do what they think is the best thing for themselves, the actual travel time for all drivers goes up! The new link, designed to reduce congestion, has made things worse. The reason lies in what computer scientist Tim Roughgarden has called “selfish routing.”Read more at location 3009
Note: c Edit
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This really brings us to the heart of traffic congestion. We are “selfish commuters”Read more at location 3017
Note: EGO Edit
A Few Mickey Mouse Solutions to the Traffic ProblemRead more at location 3053
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98% OF U.S. COMMUTERS FAVOR PUBLIC TRANSPORTATION FOR OTHERS —headline in the OnionRead more at location 3054
So how can traffic congestion, this age-old dilemma, be solved? “Build more roads!” is a typical answer.Read more at location 3056
But even if we could afford to build more roads, that might not be the best way to spend the money.Read more at location 3064
The economist Thomas Schelling points out that when each driver slows to look at an accident scene for ten seconds, it does not seem egregious because they have already waited ten minutes. But that ten minutes arose from everyone else’s ten seconds.Read more at location 3091
In traffic, the basic model has been a state-subsidized, all-you-can-eat salad bar.Read more at location 3120
Later, the Nobel Prize–winning economist William Vickrey led a long, lonely crusade to get people to accept the idea that urban roads are a scarce resource and should be priced accordingly. After all, as Vickrey pointed out in 1963, hotels charge more for in-season rooms, railways and airlines charge more for peak travel periods, and telephone companies charge more during the times when more people are likely to call—why should roads not cost more when more people want to use them?42 (Vickrey was a bit ahead of his time: Told in the early 1960s that there was no way to track where people drove, or how much they drove, Vickrey, the story goes, built a cheap radio transmitter and installed it in his car, displaying the results to friends.)43 Congestion charging, in cities like London and Stockholm, has been shown to work because it forces people to make a decisionRead more at location 3126
Once the tolls kicked in, things really began to change: People left sooner, took different routes, took buses, “collapsed” trips into shorter bundles. “The reality which is emerging is that I think people are very intelligent agents, working on their own behalf,” he said. “They understand the unique trade-off they face between time and money. The range of response is extremely broad. For instance, my willingness to pay to save ten minutes today might be very different than tomorrow.”Read more at location 3152
Cities like London are, in effect, learning from Disneyland.Read more at location 3182
Early on, Disney realized that as the park grew in popularity, managing the queues of people would prove difficult, particularly on the marquee attractions like Space Mountain. What could you do? Disney could take the approach of our traffic networks, which is simply to let an inefficient kind of equilibrium take hold. Let people wait, and if the line is too long, they may decide on their own not to get in line (or get on the highway), and thus be diverted to other rides (roads). The queue will regulate itself.Read more at location 3193
Disney tried a form of congestion pricing. It issued ticket books in which the tickets’ values reflected the capacity of the rides. Popular rides like Space Mountain required E tickets, which were more expensive than A tickets, good for tamer attractions like the Horseless Carriage on Main Street. The idea was not only to prevent people from simply lining up for the top attractions but to spread people out across the park, avoiding traffic jams at places like Space Mountain.Read more at location 3202
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Disney finally hit upon the ultimate solution in 1999, when it introduced the FastPass, the system that gives the customer a ticket telling them when to show up at the ride. What FastPass essentially does is exploit the idea that networks function both in space and in time. Rather than waiting in line, the user waits in a “virtual queue,” in time rather than space, and can in the meantime move on to other, less crowded rides (or buy stuff). People can take a chance on the stand-by line, or they can have an assured short wait if they can simply hold off until their assigned time. Obviously, FastPass could not literally work on the highway. Drivers do not want to pull up to a tollbooth and be told, “Come back at two-thirty p.m.” But in principle, congestion pricing works the same way, by redirecting demand on the network in time.Read more at location 3214
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Shreckenberg calls this the “self-destroying prognosis.” In his office at the University of Duisburg-Essen, he points to a highway map with its roads variously lit up in free-flowing green or clogged red. “The prognosis says that this road becomes worse in one hour,” he says. “Many people look at that and say, ‘Oh, don’t use the A3.’ Then they go somewhere else. The jam will not occur since everyone turned to another way. This is a problem.” These sorts of oscillations could happen with even short lags in information, in what Shreckenberg calls the “ping-pong effect.” Imagine there are two routes. Drivers are told that one is five minutes faster. Everyone shifts to that route. By the time the information is updated, the route that everyone got on is now five minutes slower. The other road now becomes faster, but it quickly succumbs to the same problem.Read more at location 3281
Chapter Seven When Dangerous Roads Are SaferRead more at location 3332
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The Highway Conundrum: How Drivers Adapt to the Road They SeeRead more at location 3333
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The Trouble with Traffic Signs–and How Getting Rid of Them Can Make Things Better for EveryoneRead more at location 3521
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Forgiving Roads or Permissive Roads? The Fatal Flaws of Traffic EngineeringRead more at location 3873
Chapter Eight How Traffic Explains the World: On Driving with a Local AccentRead more at location 3996
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“Good Brakes, Good Horn, Good Luck”: Plunging into the Maelstrom of Delhi TrafficRead more at location 3997
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“Delhi has forty-eight modes of transport, each struggling to occupy the same space on the carriageway. What other city is like this?”Read more at location 4004
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a motorized maelstrom.Read more at location 4006
They lurch, belch smoke, and ceaselessly toot their pressure horns.Read more at location 4008
“Horn Please,”Read more at location 4009
“Horn Please” originally invited following drivers to honk if they wanted to pass the slower-moving, lane-hogging trucks on the narrower roads of the past, and I was told that it endures merely as a decorative tradition.Read more at location 4010
a cacophony of claxonsRead more at location 4011
The most striking feature of Delhi traffic is the occasional presence of a cow or two, often lying idly in the median strip, feet away from traffic.Read more at location 4022
Note: VACCHE Edit
Delhi drivers have a chronic tendency to stray between lanes, most alarmingly those flowing in the opposite direction.Read more at location 4032
Delhi, where the unexpected perversely becomes the expected.Read more at location 4053
There are nearly 110 million traffic violations per day in Delhi,Read more at location 4054
Why New Yorkers Jaywalk (and Why They Don’t in Copenhagen): Traffic as CultureRead more at location 4085
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One of the first things that strikes a visitor to a new country is the traffic.Read more at location 4086
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It’s the reason a horn in Rome does not mean the same thing as a horn in Stockholm, why flashing your headlights at another driver is understood one way on the German autobahn and quite another way on the 405 in Los Angeles, why people jaywalk constantly in New York and hardly at all in Copenhagen.Read more at location 4096
Danger: Corruption Ahead–the Secret Indicator of Crazy TrafficRead more at location 4376
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In 1951, some 852 people were killed on the roads in China. In the United States in that year, 35,309 people were killed in traffic. In 1999, traffic fatalities in China had risen to nearly 84,000.31 The U.S. figure, meanwhile, was 41,508. The population of both countries had almost doubled in that time. Why did fatalities rise so much higher in China than in the United States? The answer lies in the number of vehicles in each country. In 1951, there were about 60,000 motor vehicles in China, while in the United States, there were roughly 49 million.32 By 1999, when China had 50 million vehicles, the United States had over 200 million—four times as many.Read more at location 4376
Note: CINA E USA Edit
What Smeed’s law showed was that, across a number of countries, ranging from the United States to New Zealand, the number of people killed on the roads tended to rise as the number of cars on the road began to rise—up to a point—and then, gradually if not totally uniformly, the fatality rates began to drop, as, generally, did the absolute numbers of fatalities.Read more at location 4385
The nations that rank as the least corrupt—such countries as Finland, Norway, New Zealand, Sweden, and Singapore—are also the safest places in the world to drive.Read more at location 4480
Nine Why You Shouldn’t Drive with a Beer-Drinking Divorced Doctor Named Fred on Super Bowl Sunday in a Pickup Truck in Rural Montana: What’s Risky on the Road and WhyRead more at location 4616
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Semiconscious Fear: How We Misunderstand the Risks of the RoadRead more at location 4619
When we are in traffic, we all become on-the-fly risk analysts. We are endlessly having to make snap decisions in fragments of moments, about whether it is safe to turn in front of an oncoming car, about the right speed to travel on a curve, about how soon we should apply the brakes when we see a cluster of brake lights in the distance. We make these decisions not with some kind of mathematical probability in the back of our heads—I have a 97.5 percent chance of passing this car successfully—but with a complicated set of human tools.Read more at location 4644
In most cases, when cars and trucks collide, the car bears the greater share of what are called “contributory factors.” This was the surprising conclusion that Daniel Blower, a researcher at the University of Michigan Transport Research Institute, came to after sifting through two years’ worth of federal crash data.Read more at location 4660
the reason trucks are dangerous seems to have more to do with the actions of car driversRead more at location 4672
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Should I Stay or Should I Go? Why Risk on the Road Is So ComplicatedRead more at location 4692
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“risk as analysis,”Read more at location 4693
“risk as feelings.”Read more at location 4696
It was smart of the Detroit driver to feel risk from the truck next to him, but the instinctual fear response doesn’t always help us.Read more at location 4699
In collisions between cars and deer, for example, the greatest risk to the driver comes in trying to avoid hitting the animal.Read more at location 4700
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DON’T VEER WHEN YOU SEE A DEER.Read more at location 4702
This is why, it has been argued, it has long been difficult to convince people to drive in a safer manner. Each safe trip we take reinforces the image of a safe trip.Read more at location 4715
“traffic fatalities are by far the most important contributor to the danger of leaving home.”Read more at location 4720
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Saturday and SundayRead more at location 4732
In other words, just two nights accounted for a majority of the week’s deaths in that time period.Read more at location 4733
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fatal crashes occur much less often during rush hours;Read more at location 4737
8 of every 1,000 crashes that happened outside the peak hours were fatal, while during the rush hour the number dropped to 3 out of every 1,000.Read more at location 4738
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What’s so striking about the massive numbers of fatalities on weekend mornings is the fact that so few people are on the roads, and so many—estimates are as high as 25 percent—have been drinking.Read more at location 4744
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The economists Steven D. Levitt and Jack Porter have argued that legally drunk drivers between the hours of eight p.m. and five a.m. are thirteen times more likely than sober drivers to cause a fatal crash, and those with legally acceptable amounts of alcohol are seven times more likely. Of the 11,000 drunk-driving fatalities in the period they studied, the majority—8,000—were the drivers and the passengers, while 3,000 were other drivers (the vast majority of whom were sober). Levitt and Porter argue that the appropriate fine for drunk driving in the United States, tallying up the externalities that it causes, should be about $8,000.Read more at location 4751
The most important risk factor, one that is subtly implicated in all the others, is speed. In a crash, the risk of dying rises with speed.Read more at location 4762
Solomon curve,Read more at location 4774
Solomon found after examining crash records on various sections of rural highway, seemed to follow a U-shaped curve: They were lowest for drivers traveling at the median speed and sloped upward for those going more or less than the median speed.Read more at location 4775
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“low speed drivers are more likely to be involved in accidents than relatively high speed drivers.”Read more at location 4777
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It’s not the actual speed itself that’s the safety problem, they insist, it’s speed variance.Read more at location 4780
The Risks of SafetyRead more at location 4970
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Be wary then; best safety lies in fear.Read more at location 4971
the insides of cars have been made radically safer. In the United States (and most other places), fewer people in cars die or are injured now than in the 1960s, even though more people drive more miles. But in an oft-repeated pattern with safety devices from seat belts75 to air bags, the actual drop in fatalities did not live up to the early hopes.Read more at location 4978
Were drivers trading a feeling of greater safety for more risk?Read more at location 4996
Describing what has since become known as the “Peltzman effect,” he argued that despite the fact that a host of new safety technologies—most notably, the seat belt—had become legally required in new cars, the roads were no safer. “Auto safety regulation,” he concluded, “has not affected the highway death rate.”Read more at location 5012
the increase in car safety had been “offset” by an increase in the fatality rate of people who did not benefit from the safetyRead more at location 5016
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This gap between expected and achieved safety results might be explained by another theory, one that turns the risk hypothesis rather on its head. This theory, known as “selective recruitment,” says that when a seat-belt law is passed, the pattern of drivers who switch from not wearing seat belts to wearing seat belts is decidedly not random. The people who will be first in line are likely to be those who are already the safest drivers.Read more at location 5023
The number of crashes went up, they found, while injuries went down.Read more at location 5040
I have always considered the act of wearing my seat belt not so much an incentive to drive more riskily as a grim reminder of my own mortality (some in the car industry fought seat belts early on for this reason). This doesn’t mean I’m immune from behavioral adaptation. Even if I cannot imagine how the seat belt makes me act more riskily, I can easily imagine how my behavior would change if, for some reason, I was driving a car without seat belts.Read more at location 5048