TagTraffic book

Why are children getting hurt in the street because of “looming”?

Adults are better than children at detecting the speed of a car that’s traveling faster than 20 miles per hour and are more likely to avoid crossing, thus not getting hit. 

Director of New York City-based Transportation Alternatives Paul Steely-White asked on Twitter for a plain English translation of this three-year old journal article about vehicle speeds and something called “looming”.

The article is called “Reduced Sensitivity to Visual Looming Inflates the Risk Posed by Speeding Vehicles When Children Try to Cross the Road”.

Skip to the end if you want the plain English translation, but I’ve posted the abstract below followed by excerpts from Tom Vanderbilt’s Traffic.

ABSTRACT: Almost all locomotor animals respond to visual looming or to discrete changes in optical size. The need to detect and process looming remains critically important for humans in everyday life. Road traffic statistics confirm that children up to 15 years old are overrepresented in pedestrian casualties. We demonstrate that, for a given pedestrian crossing time, vehicles traveling faster loom less than slower vehicles, which creates a dangerous illusion in which faster vehicles may be perceived as not approaching. Our results from perceptual tests of looming thresholds show strong developmental trends in sensitivity, such that children may not be able to detect vehicles approaching at speeds in excess of 20 mph. This creates a risk of injudicious road crossing in urban settings when traffic speeds are higher than 20 mph. The risk is exacerbated because vehicles moving faster than this speed are more likely to result in pedestrian fatalities.

The full text is free to download, but I think Steely-White needs to learn more now, so I pulled out my favorite book about driving, Tom Vanderbilt’s “Traffic”.

Page 95-97:

For humans, however, distance, like speed, is something we often judge rather imperfectly. Unfortunately for us, driving is really all about distance and speed. Consider a common and hazards maneuver in driving: overtaking a car on a two-lane road another approaches in the oncoming lane. When objects like cars are within twenty or thirty feet, we’re good at estimating how far away they are, thanks to our binocular vision (and the brain’s ability to construct a single 3D image from the differing 2D views each eye provides). Beyond that distance, both eyes are seeing the same view in parallel, and so things get a bit hazy. The farther out we go, the worse it gets: For a car that is twenty feet away, we might be accurate to within a few feet, but when it is three hundred yards away [900 feet], we might be off by a hundred yards [300 feet]. Considering that it takes about 279 feet for a car traveling at 55 miles per hour to stop (assuming an ideal average reaction time of 1.5 seconds), you can appreciate the problem of overestimating how far away an approaching car is – especially when they’re approaching you at 55 miles per hour.

[Here comes the keyword used in the journal article, "looming"]

Since we cannot tell exactly how far away the approaching car might be we guess using spatial cues, like its position relative to a roadside building or the car in front of us. We can also use the size of the oncoming car itself as a guide. We know it is approaching because its size is expanding or looming on our retina.

But there are problems with this. The first is that viewing objects straight on, as with the approaching car, does not provide us with a lot of information.

[...]

If all this is not enough to worry about there’s also the problem of the oncoming cars speed. A car in the distance approaching 20 miles per hour makes passing easy, but what if it is doing 80 miles per hour? The problem is this: We cannot really tell the difference. Until, that is, the car gets much closer — by which time it might be too late to act on the information.

[the topic continues]

Plain English translation

However, nothing I found in Traffic relates children and “looming”. The bottom line is that children are worse than adults at detecting the speed of a car coming in the cross direction and thus decide wrongly on when to cross the street.

Update: Based on Vanderbilt’s writing, it seems that humans cannot really be taught how to compensate for looming, to build a better perceptual model in the brain to detect the difference between cars traveling 20 and 80 MPH. If this is true, and I’d like to see research of pedestrian marketing and education programs designed for children, it may be that we should stop trying this approach.

Survivor bias: Who walks away from automobile crashes?

This photo of a damaged car has little to do with this post. 

Then my friend Alex E. asked, “Is there a reason why?”

I can’t leave such a question hanging. I thought I read that somewhere, and it was probably in Tom Vanderbilt’s book, Traffic. What I found in there mostly referred to trucks (the semi-trailer type) because of their mass and how people not driving trucks behave around them on the road. The second part explained the statistics around who lives and dies in crashes involving a drunk driver.

Knowing that, and knowing the story I tweeted a link to, you’ll see that the event didn’t involve a truck and my relating them was perhaps unsuitable. It did involve drunk driving, but I may have misread the book text.

Here’s what Traffic says about trucks

“When trucks and cars collide, nearly nine of ten times it’s the truck driver who walks away alive.” Vanderbilt discusses how that is (page 247).

…we all likely have proof of the dangerous nature of trucks. We have seen cars crumpled on the roadside. We’ve heard news stories of truck drivers, wired on stimulants, forced to drive the deregulated trucking industry’s increasingly long shifts. We can easily recall being tailgated or cut off by some crazy trucker.

Just one thing complicates this image of trucks as the biggest hazard on the road today: In most cases, when cars and trucks collide, the car bears the greater share of what are called “contributory factors”.

Really? Car drivers caused crashes with trucks and then die from it?

Instead of relying on drivers’ accounts, he [Daniel Blower at Michigan Transport Research Institute] looked at “unmistakable” physical evidence. “In certain crash types like head-ons, the vehicle that crosses the center much more likely contributed to the crash than the vehicle that didn’t cross the center line”.

After examining more than five thousand fatal truck-car crashes, Blower found that in 70 percent of cases, the driver of the car had the sole contributing responsibility in the crash.

Basically, the car drivers in a car-truck crash caused the crash and ended up being the ones dying.

…the reason trucks are dangerous seems to have more to do with the action sof car drivers combined with the physcial characteristics of trucks and less to do with the actions of truck drivers. “The caricature that we have that the highways are thronged with fatigued, drug-addled truck drivers is, I think, just wrong”, Blower said.

“In a light vehicle, you are correct to be afraid of them, but its not because the drivers are disproportionately aggressive or bad drivers”, Blower said. “It’s because of physics, truck design, the different performance characteristics. You can make a mistake around a Geo Metro and live to tell about it. You make that same mistake around a truck and you could easily be dead.”

What Traffic says about drunk driving

Of the 11,000 drunk-driving fatalities studied by economists Steven D. Levitt and Jack Porter, 72% were the crash-causing drunk driver or their passengers, and 28% were the other drivers (most of whom were not drunk themselves) (page 251).

Tell it, Sue Baker! Car crashes are not accidents

“It was an accident!”, said the driver. Photo by Katherine Hodges. 

Because of Hurricane Sandy, the New York Times paywall is down so I’m reading every article I can, starting with “Safety Lessons from the Morgue“:

As she explains it, “To say that a car crash is an accident is to say it’s a matter of chance, a surprise, but car crashes happen all the time, and the injuries that people sustain in those crashes are usually predictable and preventable.”

Another car crash-related excerpt from the article about Sue Baker, injury prevention researcher extraordinaire:

In one of her recent projects, Baker looked at another aspect of highway deaths. The study, which Baker prepared with David Swedler, a doctoral candidate, examined more than 14,000 fatal crashes involving teenage drivers. They found that male drivers were almost twice as likely as female drivers to have had high levels of alcohol in their blood and were also more likely to have been speeding and driving recklessly. Significantly, 38 percent of 15-year-old drivers, both male and female, were found to have been speeding, but by age 19, female speeders dropped to 22 percent, while male speeders remained steady at 38 percent.

Those differences, Baker says, suggest that boys and girls should not automatically receive the same driver training — and that boys should perhaps receive their license at an older age than girls. “Males might scream foul,” Baker acknowledges, “but let them.”

Yes, let them. It’s too easy to get a driver’s license in this country.  I love her style:

In 1979, at a Department of Transportation public hearing about the dangers faced by truck drivers, Baker angrily explained, “Isn’t it time we did some crash testing with trucks and dummies, rather than with drivers themselves?” Later, according to Baker, the trucking industry hired a researcher to try to discredit her driver-safety studies. Unable to uncover problems with her work, he eventually gave up and called to tell her about his assignment. [emphasis added]

Not everything is perfect with injury prevention studies, though.

In the mid-1970s, [Sam] Peltzman did research on highway fatalities that suggested that mandatory safety features like seat belts and padded dashboards actually encouraged people to drive less cautiously.

Tom Vanderbilt talked about that in “Traffic“, which is basically my favorite transportation book, even mentioning Mr. Peltzman. Flip to page 181 to read it. Vanderbilt lists all of the different labels for that behavior:

  • the Peltzman effect
  • risk homeostasis
  • risk compensation
  • offset hypothesis

He summarizes: “What they are saying, to crudely lump all of them together, is that we change our behavior in response to perceived risk, without even being aware that we are doing so”. But Sue has a response:

Baker acknowledges that there may be some individuals in cars with anti-lock brakes, for example, who may not apply the brakes as soon as they did with the old brakes. But she insists there is no evidence that better brakes or air bags have encouraged recklessness — that they have in fact saved many thousands of lives. “What concerns me,” she says, “is that these spurious arguments are used by companies to bolster their opposition to beneficial safety regulation.

I think it’s safe to say now that she’s a personal hero of mine. But way, there’s just one more thing!

As she talked about what still needed to be done, her voice was tinged with anger: “Buildings need to be designed so it’s not so easy to fall down stairs. All new homes should have sprinklers. Traffic lights should be timed for pedestrians, not to move as many cars as possible through an intersection.

Yep. Exactly what we don’t do. We make ‘em wait. And wait. Without even telling people the traffic signal’s even acknowledged their presence.

More

How high (and low) expectations can make traffic safer

I have low expectations of fellow Chicagoans who are moving their vehicles on the same roads I cycle on. I expect that every door will fling open in my path, causing me to be doored. I also expect to be cut off at any moment, and especially in certain places like at intersections (where the majority of crashes occur), bus stops, or in places with lots of parallel parking activity. Because of these expectations I feel that my journeys have been pretty safe. My low expectations cause me to ride slower, ride out of the door zone, and pay attention to everyone’s maneuvers.

This is another post inspired by Traffic: Why we drive the way we do (and what it says about us) by Tom Vanderbilt. From page 227 of “Traffic”, about expectations :

Max Hall, a physics teacher in Massachusetts who often rides his collection of classic Vespas and Lambrettas in Rome, says that he finds it safer to ride in Rome than in Boston. Not only are American drivers unfamiliar with scooters, he maintains, but they resent being passed by them: “In Rome car and truck divers ‘know’ they are expect not to make sudden moves in traffic for fear of surprising, and hurting, two-wheeler drivers. And two-wheeler drivers drive, by and large, expecting not to be cut off.”

The scooter drivers have high expectations, and it seems that they’re being met.

This all plays nicely with the “safety in numbers” theory about cycling: the more people who are riding bicycles, the more visible bicycling is, and the more aware a driver will be around people who are bicycling, and the more they will expect someone on a bicycle. Awareness means caution.

It’s difficult to gauge the safety of cycling in Chicago as we’ve no exposure rate: we don’t know how many people are cycling how many miles (nor where).

A cyclist waits for the light to change at Milwaukee Avenue and Ashland Avenue. 

Exposure rate

Exposure rate in the sense I’m using it here means the number of times someone is in a crash or injury for each mile they ride. We know how many crashes and injuries are reported each year (in the Illinois Motorist Crash reports), but we don’t know how many miles people ride (neither individually nor an estimated average).

There was a limited household survey of Cook County residents in 2008 from CMAP, called Travel Tracker, that collected trip distance information for all trips members of a household made on all trip modes – I haven’t looked into this yet.

It would be highly useful if the Chicago Department of Transportation conducted ridership counts at the 10 intersections with the highest crash rates. And if the 10 intersections changed the following year, the new intersections would just be added to the initial 10 to track the changes of the initial 10. This would be one step closer to being able to determine a “crash rate” for each intersection.

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