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Just because a speed is set higher than the limit doesn’t necessarily mean the driver intends to speed however, since adaptive cruise control is specifically designed to match the speed of vehicle in front, and mimic their speed. This means if the driver ahead decides to speed up, your ACC setting has to be higher than the limit so the sensors can stay locked on.

Although the IIHS hasn’t come to any firm conclusions as a result of the study, it’s interesting to take a look at technology that is more and more often being made standard on new vehicles and marketed as a “safety feature” and questioning whether it’s helping people drive better or not.

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By the numbers

In 2020, a total of 11,258 deaths, or 29 percent of all motor vehicle fatalities, occurred in speed-related crashes.

Based on a nationally representative sample of police-reported crashes, speeding — defined as exceeding the speed limit, driving too fast for conditions or racing — was involved in 10 percent of property-damage-only crashes and 13 percent of crashes with injuries or fatalities in 2020.

The National Highway Traffic Safety Administration (NHTSA) estimates that the economic cost of speed-related crashes is about $52 billion each year (Blincoe et al., 2015).

Drivers exceed posted speed limits on different kinds of roads. A national survey found that on interstates and other freeways, 20 percent of free-flow traffic in 2015 exceeded posted speed limits by 10 mph or more (Leonardis et al.). The percentages were similar on major arterials and on minor arterials and collectors (18 percent and 19 percent, respectively).

Speeding on all types of roads has increased. In 2007, 14 percent of free-flow traffic on interstates and other freeways, 15 percent on major arterials, and 16 percent on minor arterials and collectors exceeded posted speed limits by 10 mph or more (Huey et al., 2007).

In a 2020 national telephone survey conducted by the AAA Foundation for Traffic Safety, 45 percent of drivers said they had exceeded the speed limit by 15 mph on a freeway in the past month, and 35 percent reported exceeding the speed limit by 10 mph on a residential street (AAA Foundation for Traffic Safety, 2021).

TIP #2: Enter a Curve Slowly

Speed limits posted on curve warning signs are intended for passenger vehicles, not large trucks. Large trucks should reduce their speed even further. Studies have shown that large trucks entering a curve, even at the posted speed limit, have lost control and rolled over due to their high center of gravity.16

Did You Know? 40 percent of speeding-related fatalities occur on curves.20

Did You Know? Braking in a curve can cause the wheels to lock up and the vehicle to skid.16

An example of a driver traveling too fast for conditions is shown in the video clip below. Training exercise questions follow the video clip.

VIDEO DESCRIPTION: The CMV driver is traveling on an undivided two-lane road at night. The driver passes a curve warning sign but fails to reduce his speed. The driver is traveling too fast when he enters the curve and has trouble maintaining control of his truck. The driver has to brake hard and crosses onto the right shoulder.

TRAINING EXERCISE: After watching the video, try to answer the following questions:

  • Did the driver slow down enough to safely enter the upcoming curve?
  • What behavior indicates that the driver is driving too fast for conditions?
  • What could the driver have done differently?

Road work

Given that people aren’t assessing risk on the road logically, the newest anti-speeding research is focused on the subtle.

One widely used strategy is to put up electronic speed-feedback signs that alert drivers to how fast they’re going. While they could also glean that data by glancing at their own dashboards, the external feedback has been shown to jolt people out of their habitual patterns, Charlton says.

Engineering the environment is another way to nudge people toward slower speeds, as the Auckland experiment shows. The researchers’ studies in both driving simulators and on real roads reveal that people decide how fast to drive using cues from both the road itself and its surroundings. In a 2017 study on how drivers gauge the appropriate speed for urban roads, a research team found that roadside factors such as landscaping, houses and sidewalks cued drivers to speeds of around 30 mph (50 kph), while wider roads with painted lines prompted them to judge the appropriate speed at about 50 mph (80 kph) (Accident Analysis & Prevention, Vol. 108, 2017). In a driving simulator, people drove a little slower than what they thought the speed limit should be on the slow roads, but they tended to drive a little over the assumed speed limit on the fast-moving roads. On rural roads, one of Charlton’s studies found, people drive slower when lanes are narrower, center lines are double yellow or wide, or when traffic is heavy (Accident Analysis & Prevention, Vol. 95, Part A, 2016).

Just posting a speed limit won’t slow people down if the road “feels” fast, Charlton says. In fact, he says, mismatches between the actual speed limit and what people think the limit should be are a major barrier to getting people to drive in the right range.

“Particularly roads designed in the 1950s and ’60s and ’70s—they’re big, they’re wide…and it just feels like you should go fast,” he says. In New Zealand, there has been some effort to consider the look and feel of roads during the design phase, Charlton says, but there is still a strong emphasis on just the number of cars a road is expected to support, not how those cars will use the road. “Breaking away from just thinking about road volume and thinking about road functions is something we’re coming to grips with,” he says.

Public campaigns

“Appealing” is the watchword for one final thread of the anti-speeding effort: direct messaging. Research by Plant published in the journal Accident Analysis & Prevention found that ads viewed while off the road can make people slow down on the road, at least in the short term.

Plant and her colleagues compared the efficacy of two anti-speeding public ­service announcements (PSAs) from the Roads and Traffic Authority of New South Wales, Australia (Accident Analysis & Prevention, Vol. 100, 2017). The first, a 2004 ad called “Heaven and Hell,” starts like a standard car commercial, all macho speed and quick cuts, and ends with the driver smashing into another vehicle. The second ad, called “Pinkie,” aired in 2007 and focuses on the social side of speeding: As young men rev their engines, women trade scornful glances and outstretch their pinkie fingers, implying that the drivers are overcompensating for certain deficiencies.

After viewing one of these ads as well as an emotion-matched, non-speeding-related control ad, young drivers answered questions about how they thought the ads would influence their driving speeds, and then each took a spin in a driving simulator.

The death and destruction in “Heaven and Hell” didn’t turn out to be particularly motivational. Drivers were no slower after watching that ad than when they watched an emotion-matched PSA on another topic. But “Pinkie” was effective: Participants who had watched the sexually suggestive ad drove less speedily than those who’d viewed an unrelated, emotion-matched PSA. (Unfortunately, neither ad resulted in slower driving when participants were tested a week to 10 days after viewing.)

Interestingly, Plant says, the participants were terrible at predicting which kind of message would motivate them to slow down. Only 30 percent thought “Pinkie” would do the trick, while 70 percent predicted the carnage in “Heaven and Hell” would motivate them.

The mismatch between what drivers thought would motivate them and what actually did could be a quirk of how the researchers asked their study questions, Plant says, or it could mean people have poor insight or there is some missing link between their intention to change and the execution of said change. Either way, the finding suggests that the way researchers assess interventions might need some tweaking.

More immediately, Plant adds, the findings suggest that ads depicting social consequences for bad behavior might be more effective for young drivers than ads depicting death or injury. “Once we know the ‘how’ and the ‘why’ behind the persuasive effects of messages or interventions more generally, we can ensure that we develop effective interventions,” she says.

One exciting development on the horizon in traffic research, Plant says, is similar to the technology that Robinson and his colleagues tested to slow people down. Onboard GPS devices that can transmit real-world information about speed are likely to return much more reliable data than people’s self-reports or even data from driving simulators. Studies using such devices could lead to the development of interventions that prompt people to drive more safely on real roads.

“Observing reductions to speeding in these studies would have the most promising implications for on-road driving speeds,” Plant says.

Deadly toll
  • 9,723: Number of U.S. deaths in 2015 in which speed was directly responsible.
  • 70%: Percentage of drivers who admit to speeding at least some of the time.
  • 5.6%: Increase in crash fatalities from 2015 to 2016.
  • 4%: Increase in fatalities due to speed-related crashes from 2015 to 2016, from 9,723 to 10,111.

Source: U.S. National Highway Traffic Safety Administration