Speed kills – when you’re injecting or snorting it. The reality on the roads, as you’re about to learn, is far more complex.
This article explores the relationship between speed, accidents, and road fatalities on rural roads and highways. The relationship between speed on accidents in urban areas is a topic for another article, as it presents a different dynamic confounded by factors such as increased traffic densities, far greater potential pedestrian-vehicle interactions, and a far greater incidence of vehicles interrupting flow of traffic by entering/exiting driveways and intersections.
The Early Research: Speed vs Accidents on U.S. Highways
In 1964, the U.S. Department of Commerce / Bureau of Public Roads released a report entitled “Accidents on main rural highways related to speed, driver, and vehicle“. The first nationwide study of its kind, it examined the relationship between speed and the characteristics of vehicles/drivers involved in road accidents on 2- and 4-lane rural highways.
To determine the speeds of crashed cars, the researchers used state accident reports for 10,000 drivers involved in accidents on the 600 miles of studied highways. The travel speeds of these drivers were used – not the speed at the moment of impact, but the normal speed of the driver before they became aware of an impending accident.
To determine what if any risk was conferred by travelling at speeds lower or higher than the surrounding traffic, the speeds of accident-involved vehicles needed to be compared to average traffic speeds. To determine the average speeds of traffic on the studied roads, the researchers initially made numerous test runs driving a vehicle with the flow of traffic and noting the speed. They then further recorded the speeds of 290,000 individual drivers at 35 selected sites using a concealed speed detection device. At a distance beyond and well out of sight of the speed observation points, the drivers were stopped and interviewed to obtain information on other characteristics such as the driver’s gender, age, military status, and residence; the type of vehicle; and the seated locations of any passengers.
Needless to say, this was a very large and thorough study. Among the its findings were that the severity of accidents increased as speed increased, especially at speeds exceeding 60 mph (97 km/h), and that the fatality rate was highest at very high speeds.
This appears to support the anti-speed paranoia emanating from Australian governments and police forces, yet you will never see them citing this report. There’s a reason for this: The remainder of the report refutes all of their nonsensical anti-speeding propaganda.
An Ounce of Prevention…
Motor vehicle accidents are a bit like violent confrontations: The easiest and best way to survive them is to avoid them in the first instance.
Which brings us to the two key findings of the 1964 study, which was authored by David Solomon.
Check out the graph below, which shows the risk of accidents according to vehicle speed.
As the graph clearly shows, during both daytime and night-time hours, the accident rate was by far highest for the very low-speed drivers.
During the day, the lowest accident rate ocurred at around 65 mph (105 km/h), and beyond that began to increase.
Higher overall accident risk occurred at night, where the lowest accident rate was seen at around 55 miles per hour.
Perhaps the most important finding of all was that “the greater the differential in speed of a driver and his vehicle from the average speed of all traffic, the greater the chance of that driver being involved in an accident. For example, a driver traveling at 40 or 80 miles per hour in relation to an average speed of 60 miles per hour for all traffic has a substantially greater chance of being involved in an accident than a driver traveling at the average speed.”
This was captured in the following graph, which shows that a driver’s accident risk increased the further his speed deviated from the average speed of surrounding drivers.
The distribution curve seen in the above graph became known as the “Solomon Curve”.
Further evidence that the “Speed Kills” paradigm is an overly simplistic one came from another of the report’s findings:
“… drivers 40 years of age, traveling at 65 miles per hour in cars 2 years old that had 200 horsepower, averaged only one reported accident in 1,600,000 miles of driving. In contrast, drivers 18 years of age, traveling at 30 miles per hour in cars 6 years old that had 100 horsepower, averaged one reported accident in 12,000 miles of driving.”
In other words, an 18 year old driving a 100 hp vehicle at 48 km/h had 133 times the crash risk of a 40 year old driver travelling at 105 km/h in a 200 hp vehicle.
And so all the way back in 1964, Solomon was showing that the relationship between vehicle speed and road accidents was a far sight more complicated than the mindless “Speed Kills” mantra favoured by our duplicitous governments. Such factors as driver inexperience, vehicle characteristics, and excessively high and low speeds all increased the risk of having an accident.
“Thus,” wrote Solomon, “within the limits of the study, there is an unmistakable inclination that low-speed drivers are more likely to be involved in accidents than relatively high-speed drivers. Note that at extremely high speeds, approaching 80 miles per hour [129 km/h], the difference would disappear.”
One key potential confounder was the effect of intersections, where collisions often involve at least one slow moving vehicle. To minimize this confounder, Solomon analysed road sections with as few intersections as possible and no major intersections were included. Nonetheless, some of the reported accidents did occur at intersections and, as Solomon acknowledged, many of these intersection accidents “probably involved at least one relatively slow moving vehicle. Thus in the speed range of 10-30 miles per hour, it is conceivable that up to half of the accident involvements occurred at intersections.”
Thus, the risk curve for low speeds could have been influenced by cars travelling momentarily slow as they navigated intersections. But according to Solomon, “even if the data for these accidents mere eliminated, the portion of the curve for low speeds in figure 2 would be reduced only a fraction of a log unit. The basic findings of the study would not be affected; that is, the accident involvement rate is lowest at about the average speed of all traffic and highest at the very low speeds and the very high speeds.”
Subsequent Research Confirms the Solomon Curve
In 1968, Julie Cirillo published a report in US Federal Highway Administration journal Public Roads confirming Solomon’s findings on speed variability and accident risk. Two thousand vehicles involved in daytime crashes on interstate highways were analysed. Data were collected on rural and urban section of interstate highways from twenty state highway departments.
“On the interstate system,” wrote Cirillo, “as the speed of a vehicle varies from the mean speed of traffic, either above or below the mean speed, the chance of the vehicle being involved in an accident increases. The level of enforcement has little or no apparent effect on the mean speed or on the accident experience of a study section. Proximity to interchanges, especially in urban areas, appears to affect significantly the accident experience of the study section.”
The similarity between Cirillo and Solomon’s findings can be seen in the graph below.
One limitation of Cirillo’s analysis is that it did not include single vehicle accidents – it took into consideration only crashes involving two or more vehicles (rear end, same direction sideswipe or angle collisions). Solomon had found the proportion of single vehicle accidents increased at higher speeds, so Cirillo’s omission of single vehicle accidents could have potentially introduced a favourable bias for higher speeds.
In 1970, the Research Triangle Institute published the results of a study that used a combination of trained on-scene crash investigators and a system of automated speed monitoring sensors embedded in the roadway to measure the speed of crash-involved vehicles at the time and location of the crash. Data were collected on 114 crashes involving 216 vehicles on a state highway in Indiana with posted speed limits of 40 to 65 mph. The investigators were able to differentiate vehicles slowing down to negotiate a turn from vehicles moving slowly in the flow of traffic. After deleting the data for turning vehicles, they risk at lower speeds was reduced when compared to the results of the Solomon and Cirillo studies. Nevertheless, the accident risk still increased markedly for vehicles deviating 15.5 mph above or below the average traffic speed[3,4]. The graph below shows the U-curves for all accidents, and non-turning accidents only:
As RTI researchers West and Dunn noted in a 1971 follow-up report:
“A person involved in a low-speed accident is, of course, less likely to be injured but he is also more likely to be involved in an accident.”
Here’s a quick pop quiz for readers:
Would you rather travel at a higher speed and increase your chance of avoiding a road accident altogether, or would you rather travel at a lower speed, increase your risk of being involved in an accident, and hope that your lower speed minimizes your risk of injury or death?
We don’t know about you, but we’d take the first option every time. Even non-casualty accidents are a great way to ruin your day, and it’s a safe bet you’ll emerge unscathed from 100% of the accidents you avoid.
The Solomon, Cirillo and RTI papers are probably the best known and most discussed on the subject, but plenty of other studies have found similar results. Here’s a quick discussion of some of those studies:
Munden (1967) investigated the connection between a driver’s characteristic speed and accident rate. The speed and registration numbers of over 31,000 cars were recorded at 10 sites on main rural UK highways. The speed ratio for each car was calculated by dividing its observed speed by the mean speed of the 4 automobiles preceding and 4 automobiles following it.
Many vehicles were observed several times and the mean ratios were obtained for these vehicles. The accident rates of more than 13,000 of the observed cars were obtained from local police. Among drivers observed more than once, those traveling more than 1.8 standard deviations above or below the mean traffic speed had significantly higher crash rates while the average speed drivers had the lowest crash rates. Drivers observed only once did not exhibit this U-shaped relationship.
Hauer (1971) analysed the risk of overtaking, and found the number of vehicle interactions, in terms of passing or being passed, is a U-shaped curve with a minimum at the median speed. That there will be less passing when vehicles travel identical speeds should come as a surprise to no-one. Nor should the key finding from this study, which was the increased risk of crash involvement as a result of potential conflicts when a faster vehicle passed a slower vehicle. Again, when traffic is flowing in unison and minimal passing or overtaking is occurring, there is far less potential for collisions.
Lave (1985) collected nationwide average speed and 85th percentile speed data for 6 different types of highways (rural and urban interstates, arterials and collectors) from 48 states for 1981 and 1982. Speed dispersion was calculated as the difference between 85th percentile speed and the mean speed. Speed, by itself, was not found to have a significant effect on fatality rates. However, when using speed variance as the main variable, 10 out of 12 road types showed a statistically significant increased fatality risk.
Harkey, Robertson and Davis (1989) also observed a U-shaped relationship between speed and accidents on urban roads in Colorado and North Carolina. The police estimated travel speeds of 532 vehicles involved in accidents over a 3-year period and compared them to the 24-hour speed data collected on the same road. To make the crash and speed data more comparable, the analysis was limited to non-intersectional, non-alcohol and weekday crashes. The minimum crash rate was observed near the 90th percentile of travel speeds.
Fildes and Lee (1993) studied speed and traffic safety in Australia and did not find the U-shaped relationship between speed and crash risk, but rather a linear relationship. They did, however, confirm the relationship between speed variability and accident risk. As a vehicle deviated from the mean traffic speed, the probability of being involved in a crash increased much more significantly on urban roads, compared to the probability on rural roads, probably because of the higher traffic volumes on urban roads.
Finch, Kompter, Lockwood and Maycook (1994) collected international speed and accident data and performed a regression analysis to study the relationship between speed and accidents. They found the probability of being involved in an accident was represented by a U-shaped curve as a function of speed.
Cameron, Newstead and Vulcan (1994) conducted a study in Victoria, Australia to study the reasons behind a reduction in road fatalities from 776 in 1989 to 396 in 1992. Although it was a “factor” (the F-word again!), the authors concluded the reduction in speed limit from 110 km/h to 100 km/h (68.35 to 62.14 mph) was not the main reason for the reduction in fatalities. There were other factors involved in the reduction, such as increased enforcement, increased public awareness, and improved road systems.
Liu (1998) examined accident data from 1969-1995 in Canada and observed that on roads with higher speed limits, as the average speed increased both the speed variance and the fatality rates decreased.
Coffman, Stuster and Warren (1998) conducted a literature review of all American and international research to analyse the relationship between speed and accidents. It was concluded that the crash risk is lowest near the average speed of traffic and increases for vehicles traveling much faster or slower than traffic.
Garber and Ehrhart (2000) found that, as the mean speed increased, the crash rate decreased slightly until the mean speed reached the posted speed limit of 65 mph, and then the rate began to increase. The crash rate also increased as the mean speed increased beyond the speed limit. It was noted that the changes in crash rates were not necessarily caused by any one independent factor. The changes were a result of the combined effects of independent factors like speed, standard deviation, and traffic flow.
Rajbhandari and Daniel (2002) examined the effects of increase from 55 mph to 65 mph limits in New Jersey in 1998. The data were collected from 1997-2000. During this period, they observed a 27% increase in overall accident rates, but increased speed variance seemed to explain much of the increase. The increase in speed limit to 65 mph caused more speed variance between automobiles and trucks and increased the accidents that involved trucks by 19%.
Fitzgerald (1989) studied the increase in the speed limit of trucks from 80 km/h to 90 km/h, while retaining the 100 km/h speed limits for automobiles in Australia. The average speed difference between trucks and automobiles was reduced from 10 km/h to 8 km/h, thus reducing the speed variance. It was also found there was no significant change in the accident rate that could be attributed to the change in the truck speed limit.
So we can see the findings of Solomon, Cirillo and the RTI were hardly fluke results: A large volume of research has since confirmed their observations on speed variance and also, in many instances, the U-shaped relationship between traveling speed and accident risk. As Steven L. Johnson and Naveen Pawar note in their extensive review of speeding research, “Although there is a large amount of controversy over the magnitude of the effect that increases in posted speed limits have on highway safety, there is a relatively strong consensus among both researchers and practitioners that a higher variance of vehicle speeds in the traffic flow increases the risk of accidents.”
As for the research examining speed limits and their relationship to accident risk, Johnson and Pawar noted:
“Unfortunately, many of the studies involve more advocacy than science. One section of this report addresses the methodological issues associated with much of the research on the relationship between speed limits and highway safety. For example, the studies that analyzed the number of fatalities during the transition periods immediately after speed limits were increased often found very large increases in the number of fatalities. However, other studies that measured fatality rates or accident rates over a longer time frame often concluded that there was little or no negative impact of the speed limit increases.”
Similarly, many sources in the popular press refer to the statistics that indicate that more than one-third of the highway accidents are associated with “speeding.” However, speeding is defined as ‘traveling faster than the posted limits’ or ‘traveling too fast for conditions.’ Because there is no differentiation of these two categories in much of the literature, the effect of the posted speed limits on the number of accidents and fatalities is probably highly exaggerated in the popular literature.”
The Johnson and Pawar report is well worth a read, and can be freely downloaded in its entirety here:
Lies, Damned Lies, and Australian Government-Sponsored Research
One of the studies discussed by Johnson and Pawar that absolutely reeks of involving “more advocacy than science” was published in 2001 by the Road Accident Research Unit (RARU) at Adelaide University in South Australia. We’ve seen this and an earlier RARU study referenced numerous times in Australian anti-speeding propaganda, yet mention of the Solomon, Cirillo, RTI and similar studies in said propaganda remains rarer than an honest politician.
The RARU study, it should be noted, was sponsored by the Commonwealth Government’s Australian Transport Safety Bureau. Not only was the study sponsored by the Commonwealth Government, but it was published by the Commonwealth Government. Therefore, it was not subject to the kind of independent analysis that would have occurred had it been published in a reputable peer-reviewed journal.
This is an important consideration, because Australian governments are among the most voracious users of speed detection equipment in the world. Increasing public scepticism towards the highly lucrative speed enforcement system has left Australian governments eager to seize upon any ‘evidence’ that their highly punitive anti-speeding campaigns are all about public safety and not opportunistic revenue raising.
And so when you have an Australian government-sponsored study that just happens to support the speeding enforcement agenda of Australian governments, all the while contradicting the findings of most previously published research, one cannot help but be suspicious. Indeed, given the long, well-documented history of truth-twisting and outright dishonesty exhibited by Australian governments, one should be suspicious.
The RARU staff would no doubt insist they are all wonderfully ethical and impartial individuals, as most people would instinctively insist of themselves. All we will point out here is the well-established observation that studies conducted or sponsored by entities with a vested interest in the outcome are far more likely to return results favourable to said entities, than those conducted by parties with no vested ideological or financial interest. Readers should keep this in mind, along with the discussion that follows, then decide for themselves whether it’s a good idea for researchers subject to such potential conflicts of interest to conduct speeding ‘research’ that is used to make sweeping recommendations to increase speeding fines, reduce speed detection tolerances, and even intensify government efforts at social conditioning.
Here at SCS, we have little doubt as to whether the research emanating from outfits like the RARU constitutes advocacy as opposed to science. Ever since examining the appalling research emanating from the Monash University Accident Research Centre (MUARC) in Victoria – which you can read all about here – we’ve developed a very deep scepticism for the government-sponsored road safety research departments at Australian universities. The substandard methodologies employed and the untenable conclusions reached by these so-called ‘research’ departments leads us to assume they are either terribly incompetent, or heavily influenced by the anti-speed agenda of their government sponsors.
The Adelaide University report, authored by Kloeden, Ponte and McLean, does little to alter our scepticism. Be warned: If you are offended by harsh criticism, you’d best leave this page now. The following critique is quite unforgiving of Kloeden et al, for the following reasons:
- Sloppy, biased methodology and hypocrisy. Kloeden et al are themselves quite unforgiving in their criticisms of the Solomon, Cirillo, and RTI studies, dismissing them as “biased”, but the Adelaide researchers then proceed to conduct a hopelessly biased study of their own. Keep in mind Solomon, Cirillo and the RTI published their research in the 1960 and 1970s, when research into speeding and road safety was still in its infancy, and hence the field’s scientific methodologies were still in very early stages of development. Some three decades later, with the benefit of much hindsight and a wealth of subsequent research published by other authors, Kloeden et al cannot even begin to lay claim to the same excuse.
- Propaganda. Science is supposed to be an impartial and objective search for the cold hard facts. Science is not supposed to act as propaganda, and therefore is not meant to facilitate dubious government agendas, such as the implementation of increasingly draconian laws whose only proven effects are the raising of extra government revenue and the imposition of further restrictions on the public. Yet after presenting a terribly deficient paper, Kloeden et al have no qualms about recommending a number of draconian and punitive measures, along with intensification of government propaganda efforts in order to create a “culture of compliance”, all based on the findings of their wholly inadequate research. Any attempts by governments to pass and enforce self-serving laws that restrict civil freedoms without any benefit to the public, only to said governments, should be vigorously opposed at every turn. As should any poorly-contrived research that supports such self-serving government behaviour.
Regarding point #1 above: In research papers, it is customary for researchers to discuss the findings of previous and similar research, before presenting their own findings. These discussions often comment on the strengths and weaknesses of previous research. Discussing the limitations of previous research is perfectly valid and an important part of the quest to produce research of ever-improving quality. However, when researchers make much ado about the weaknesses of a relatively small sample of prior studies that just happen to contradict their own preconceived biases, then proceed to conduct a study of their own that is even more flawed than those they have criticized, then what we are left with is a rather ironic excursion into incompetence and/or hypocrisy (or both).
The Kloeden et al paper of 2001 begins:
“Excessive speed is reported to be an important contributory factor in many crashes.”
How much, exactly, is “many”?
“Analyses of a number of large data bases in the United States indicated that speeding or excessive speed contributed to around 12 per cent of all crashes reported to the police and to about one third of fatal crashes (Bowie and Walz, 1991).”[Bold emphasis added]
If that passage was written by someone free of anti-speeding bias, it could just as easily read:
“Analyses of a number of large data bases in the United States indicated that speeding or excessive speed was not involved in 88 per cent of all crashes reported to the police nor two-thirds of fatal crashes.”
In other words, large US databases indicated speed had nothing to do with 9 out of 10 road accidents, nor the overwhelming majority of fatal accidents. Therefore, the most productive avenues for decreasing both the overall accident rate and the death toll are clearly to be had from measures other than speed reduction and enforcement.
Kloeden et al, however, didn’t give up that easily.
They wrote of Australia, “it has been reported that excessive speed is an important factor in approximately 20 per cent of fatal crashes (Haworth and Rechnitzer, 1993) and speed is a probable or possible cause in 25 per cent of rural crashes (Armour and Cinquegrana, 1990).”[Bold emphasis added]
Note how they avoided stating outright that speed directly causes these crashes (a claim for which they would have no proof) and instead engage weasel words like “factor”, “probable” and “possible”.
In an attempt to strengthen their terribly flimsy anti-speed foundation, Kloeden et al added the following piece of gobbledegook:
“It has been argued that such figures are likely to under-estimate the role of speed in crashes because subtle effects, such as the amplification of other dangers in the traffic situation by relatively small increases in speed, are likely to be overlooked (Plowden and Hillman, 1984).”
Here, Kloeden et al were attempting to add weight to their anti-speeding stance by citing a 1984 booklet by UK researchers Plowden and Hillman that “argued” speed might amplify “other dangers in the traffic situation”. Note their use of the phrase “It has been argued”; yet more weasel wordsmithery designed to infer something for which they have insufficient evidence to state outright. People argue all manner of things, from who will win this year’s AFL grand final to whether chocolate is bad or good for you (for the record, we argue the latter). Heck, there are still people that argue the Earth is flat. Needless to say, just because someone argues something, does not even begin to mean it has any basis in fact.
And so right off the bat, it is clear Kloeden et al had already made their minds up that speeding was a major cause of motor vehicle accidents, even though the US research they cited indicated otherwise, and the Australian and UK evidence they cited amounts to little more than speculation. As it turns out, Kloeden et al had previously published a paper, in 1997, claiming that, in metropolitan Adelaide, a 5 km/h increase above the 60 km/h limit led to a 200% increase in casualty crash risk, while traveling at 10 km/h led to a 400% increase in casualty crash risk. [Bold emphasis of “casualty” added, for reasons to be elucidated shortly]
In that 1997 report, the authors even made the absurd claim that mild speeding is as dangerous as driving with over twice the allowed blood alcohol concentration!
“… the relative risk of involvement in a casualty crash at 72 km/h,” they claimed, apparently with straight faces, “ is similar to that for a BAC of 0.12.”
Lo and behold, the sole evidence for this reckless and wholly irresponsible claim was to compare the crash speed data from their 1997 data with the BAC data of casualty crash drivers from a small study published by the RARU itself back in 1980. Meaning, the researchers did not compare BAC versus speed and crash risk among the same sample of drivers, but among samples of drivers collected almost twenty years apart: Two different generations of drivers, driving different cars, on different roads. In layman’s terms, this is known as “comparing apples with oranges”; (competent) researchers call it “inappropriate extrapolation”.
If only Kloeden et al stopped referencing themselves, and instead examined the research on the effect of alcohol versus speeding, they would have learned the following:
-If you drink and drive, then by the time you’ve reached the legal U.S. BAC limit of 0.08, you have already multiplied your risk of being killed in a single-vehicle crash by eleven to fifty-two-fold, the level of risk varying with age.
Here in Australia, the legal BAC limit is 0.05. But no matter: Even at BAC levels of 0.02 to 0.049, the risk of being killed in a single-vehicle crash increases three- to five-fold.
Why is drink driving so much more dangerous than Kloeden et al were prepared to acknowledge?
Because when a driver is inebriated, his/her focus and coordination becomes impaired, and his reaction time is greatly slowed. A 2000 review of 112 studies provides strong evidence that impairment in driving skills begins as soon as BAC departs from zero. The majority of these studies reported impairment at a BAC of 0.05 percent, while virtually all drivers tested exhibited impairment on some critical measure of driving performance by the time they reached a BAC of 0.08.
The aforementioned research on alcohol was published in 2000, so Kloeden et al could have published a correction of their earlier nonsensical 1997 statement in their 2001 paper.
They didn’t. Which means they either ignored this inconvenient research, or they were truly unaware of it. The first possibility equates to intellectual dishonesty, the second begs the question of why folks like us, who don’t get paid a whit to put together this information, were able to easily find and read this research, while researchers being paid handsomely to keep abreast of road safety research could/would not?
The very real influence of alcohol upon road accident risk is a major driving factor behind the decrease in the Australian road toll that occurred during the 80s, 90s and early 2000s.
The government fetish for speed enforcement, in contrast, has achieved little, and is now leaving Australian governments impotent in the face of recent increases in the road toll; increases that, in the face of draconian speed enforcement, are no doubt due to other factors such as drug use and the use of mobile phones while driving.
Why has the obsession with speeding proved so unfruitful? Because as a driver increases his vehicle speed, his focus improves and his reaction time is decreased. Read that again: The faster you go, the better your focus and reaction time. This doesn’t mean the safest speed is to travel as fast as your car will allow; eventually there will be a trade-off between your improved focus and reaction time and your ability to safely travel at a speed commensurate with your vehicle handling skills, your vehicle’s handling and braking capabilities, and the prevailing road conditions. But in the range of speeds traveled by reasonable, non-kamikaze drivers, this has huge implications for road safety, particularly on longer road journeys. Driver distraction and fatigue is a major factor in road accidents (and while authorities seem to appreciate the effect of fatigue in the case of truck drivers, they seem blissfully indifferent to it in the case of car drivers, save for the occasional and ineffectual “Tired: Take a Powernap” sign on some rural highways).
What do you think is likely to happen to driver distraction and fatigue on rural road trips when you force drivers to drive slower than they normally (and quite reasonably) would?
Yes, it will very likely worsen. Indeed, this has been cited as a major reason behind the observation that higher speed limits on rural highways are often accompanied by reductions in the accident rate and road toll.
Not the kind of research findings Kloeden et al and their government sponsors are fond of citing, but they’re true and there in the literature for all to see. Just why Kloeden et al ignored this research and instead deferred to their own small study from 1980, they never explained.
Their rampant anti-speed bias was also glaringly evident when they wrote the following in their 1997 paper about a 1994 paper by Lave and Elias:
“Lave and Elias (1994) argued that the 65 mph limit saved lives when the change was evaluated at a system level. In their model, Lave and Elias considered not the fatality rate for particular roads or collections of roads, but fatalities rates for states as a whole. They argued that the increased speed limit might confer a safety benefit through encouraging more traffic to use the interstate highways which were of superior design and therefore safer than other roads, and through allowing police resources to be directed elsewhere resulting in improved safety on other roads.”
Sounds like commonsense to us, but not to Kloeden et al, apparently. They complained:
“This is not the place for a full discussion of the potential pitfalls of the approach of Lave and Elias, suffice to say that as the outcome variable used (in this case, statewide fatality rate) becomes more distant from the event of interest (changes to speed limit on only a few roads), it is increasingly difficult to interpret results of a model which inevitably over-simplifies a complex situation. The point to be made in the context of the current review is that Lave and Elias do not argue that the 65 mph limit roads themselves became safer than they were when the limit was 55 mph.”
Before we discuss what is so wrong with the above passage, we want to show you a graph depicting road fatality rates in the USA prior to and then after the national speed limit was increased from 55 mph to 65 mph:
This graph clearly shows that after the speed limit was increased to 65 mph, the road toll continued to decline. We don’t care what convoluted poppycock folks like Kloeden et al employ in an attempt to downplay this inconvenient observation, a decline in the road toll is unquestionably a good thing.
Now let’s examine their above passage a little more closely. Kloeden et al wrote:
“This is not the place for a full discussion of the potential pitfalls of the approach of Lave and Elias”.
Why not? Lave and Elias made some very important observations, the potential life-saving ramifications of which cannot be lightly dismissed. But while Kloeden et al had little trouble devoting time and space to dissect and dismiss the Solomon, Cirillo and RTI studies, when it came to the inconvenient findings of Lave and Elias, suddenly they ran out of time and space?
They then complained the “outcome variable used (in this case, statewide fatality rate) becomes more distant from the event of interest (changes to speed limit on only a few roads)”
This piece of utter non-brilliance immediately brings to mind the old adage “they can’t see the forest for the trees”. Kloeden et al seemed to have lost sight that the primary goal of road safety measures is saving lives and reducing serious injury; not merely to reduce fatalities on selected stretches of road, but to reduce overall fatalities. What’s the point of making selected stretches of road safer if overall road fatalities statewide continue to rise?
And then there’s their cracker, “it is increasingly difficult to interpret results of a model which inevitably over-simplifies a complex situation”. This is a most curious comment coming from researchers who, as you are about to learn, have done just that themselves.
So rather than celebrate the overall decline in the US road toll that has accompanied the national speed limit increase from 55 mph to 65 mph – and a drop in road deaths is definitely something to celebrate – Kloeden et al grudgingly gave it a nod (at least at state level), but then whined about oversimplification of a “complex” situation.
Dear Kloeden et al: The US speed limit went up. The US road toll went down. That’s a good thing.
Okay, so we’ve established that Kloeden et al were anything but neutral when embarking on the study reported in their 2001 paper. It appears that at least since 1980, there has been a (highly mistaken) belief in their RARU department that relatively low-level ‘speeding’ is as bad as drunken driving, and the authors themselves have clearly revealed their anti-speed bias in a previous 1997 paper.
So let’s take a look at their 2001 paper in detail. After presenting the results of their study, the authors concluded:
“Even a 5 km/h reduction in the speed of all the rural free travelling speed vehicles would lead to a 31 per cent reduction in these casualty crashes. It was also found that 24 per cent of all the casualty crashes investigated would have been avoided if none of the vehicles had been travelling above the speed limit and that lowering the maximum speed limit on undivided roads to 80 km/h could be expected to lower casualty crash frequency by 32 per cent. This indicates the considerable safety benefits possible from a reduction in rural travel speeds.”
So how, exactly, did the authors arrive at this conclusion, which was no doubt music to the ears of governments and speed enforcement units Australia-wide?
The authors included in their analysis only casualty crashes that occurred on rural roads from March 1998 to March 2000 within a 100 km radius of Adelaide.
And here we see the first glaring problem with the Kloeden et al paper:
Yep, the exact same flaw they so readily accuse other research efforts of suffering.
We already know from research going back decades that if a motor vehicle accident occurs, then the severity of that accident is likely to be greater at higher speeds. No-one is disputing this, and I think most people would consider it common knowledge the greater the velocity with which one object hits another, the greater the subsequent damage from that collision will likely be.
Sadly, this is where Kloeden et al’s understanding of the relationship between vehicle speed and road accidents seems to end. They accuse other researchers of over-simplification, yet they themselves display a terribly simplistic view of speed and accident causation.
As noted above, Kloeden et al’s study blatantly ignored all but casualty crashes; i.e., those resulting in hospitalization or death. This automatically instills a number of irreversible biases into the study.
First of all, by only considering casualty crashes, the authors are setting the study up to confirm their pre-existing belief that speeding is dangerous. Again, that higher speeds can exacerbate the severity of motor vehicle accidents is not news to anyone. One hardly needs to be a genius to know what the study is likely to find when its authors have conveniently cast aside data for non-injurious vehicle accidents and included only casualty crashes.
So it’s at this point we’d like to introduce Kloeden et al to another time-proven piece of wisdom:
An ounce of prevention is worth a pound of cure.
Remember our previous analogy about violent confrontations? You might be one of the most skilled and most ferocious fighters on the planet, but if you make a habit of getting into violent confrontations, there’s a good chance lady luck will eventually catch up with you, in the form of someone who happens to be even more skilled and ferocious, multiple opponents, or opponent/s who happen to be armed with weaponry that negates your bare-handed fighting prowess.
Meanwhile, picture a slightly-built person with poor combat skills, who would have no chance against you in a one-to-one match up. However, this person also understands his/her physical limitations and hence not only avoids seeking violent encounters but also conscientiously avoids locations and situations where these encounters have a statistically higher probability of occurring.
Again, in a one-to-one match-up, you’d have little problem kicking this person’s posterior. Nonetheless, this person still stands an excellent chance of enjoying a longer lifespan than you, for one simple reason:
They are far less likely to get into violent confrontations, and violent confrontations can be deadly.
That’s why, if you ever have the good fortune of attending a self-defense seminar by such fighting experts as Canada’s Richard Dimitri or the UK’s Lee Morrison, you’ll notice something interesting: Despite their advanced fighting skills, before these guys teach you a single fight technique they will give you and your fellow seminar attendees a lengthy dissertation on such concepts as situational awareness and conflict de-escalation. These guys might be fearsome fighters, but experience has demonstrated to them repeatedly that the best way to survive a violent encounter is to avoid it in the first instance.
So what does all this talk about fighting have to do with road safety?
Motor vehicle collisions are another form of violent confrontation, only they involve heavy metallic objects instead of brawling humans. And the best way to emerge unscathed from a motorized violent confrontation is to avoid it in the first instance.
You see where this going? If so, congratulations, because you clearly have far more foresight than a lot of Australian road safety researchers.
Whatever the effect of speed on motor vehicle accident severity, if you reduce the overall incidence of motor vehicle accidents then there is an excellent chance you will concomitantly reduce the overall road death toll. The reason is simple: You have reduced the number of opportunities for fatalities to occur.
That’s why the “Speed Kills” mantra is an overly simplistic and intelligence-insulting one. It’s kind of like having a heart attack: Whatever life-saving drugs or spectacular surgical procedures are available, you’d be far better off not having a coronary event in the first place, because the best chance of survival comes from remaining heart attack-free.
So … what if higher speed limits on rural roads, while doing little to reduce the severity of high speed accidents, endowed other benefits that led to a reduction in the overall accident rate and a concomitant reduction in road deaths? As we’ve seen, there is already a wealth of research to suggest this can and does happen, but Kloeden et al aren’t having any of it.
They’re clearly not interested in the relationship between speed and overall accident rate, so they simply ignore it.
As if that’s not bad enough, even their highly selective focus on casualty crashes is a very dubious and non-representative one. Take a look at the following tables from their paper:
Table 3.1 contains all the accident cases that made it into Kloeden et al’s highly selective analysis. Note that only 167 crashes were included.
Table 3.2, meanwhile, contains rural casualty accidents in South Australia from 1997 alone. These include accidents outside the 100 km radius from Adelaide, and also accidents occurring within rural townships. The total number of accidents in this table is 1,500 (not 167, as the authors erroneously entered in the total number field). Even after allowing for removal of the relatively small proportion of accidents occurring within townships on roads with <80 km/h speed limits, that is a humongous difference in the accident count.
Assuming a similar rate of investigated accidents in 1998, this means around 3,000 rural casualty accidents were occurring biannually in South Australia in the late 1990s. Which means Kloeden et al included a piddling 5.5% of all casualty rural accidents in their analysis. The researchers had a long list of exclusion criteria, most of which are depicted below:
In addition, the researchers were on call to attend crashes from 9:00 am to 5:00 pm, Monday to Friday, during the day Saturday and Sunday, and also Thursday and Friday nights. Some fatal crashes that occurred outside these times were investigated on a “follow-up basis”.
Furthermore, the researchers claim that in some locations the traffic volume was too low to collect enough control speeds and in others the road conditions or speed limits on the roads changed soon after the crash meaning that comparable vehicle speeds could not be collected. This led to even more casualty crashes being dumped from the analysis.
So with their imposition of a 100 km radius, their own time restrictions for attending accident scenes, insufficient/unavailable control speed data for some locations, and a lengthy list of exclusion criteria, Kloeden et al deleted all but 5.5% of casualty crashes from their analysis. It is a major cause for concern when a study seeking to determine the role of speed in casualty crashes omits a whopping 94.5% of reported casualty crashes. Such a minute sample can hardly be considered representative of casualty crashes in general.
Indeed, when we examine tables 3.1 and 3.2 above, we see fatal crashes account for a hefty 28.1% of accidents investigated by Kloeden et al, but a minuscule 4.8% of the 1500 casualty crashes reported for 1997.
Kloeden et al even acknowledge:
“If, as is generally assumed, higher travelling speeds are associated with more serious crashes then the current analysis may introduce a bias towards higher risk estimates for casualty crashes as a whole. Since the existence or size of this effect is unknown it is more precise to say that that our risk estimates are based on a higher than average level of crash severity.”
After this brief flirtation with reality, however, Kloden et al promptly resume business as usual and carry on as if this critical flaw is of little consequence.
This is a Joke, Right?
The section of the Kloeden et al paper that truly leaves us shaking our heads is the section where they discuss their methodology for determining the average speed of cars involved in their tiny sample of casualty accidents, and the average speed of cars traveling on the same section of road that were not involved in accidents. In terms of methodology, this is by far the most important aspect of their paper, because the average speed of crash vehicles is compared to the average speed of the crash-free “control” vehicles and then used to draw conclusions about the role of speed in casualty crashes.
The method for determining the speed of vehicles involved in their miniscule sample of casualty crashes involved a mix of on-site investigation, interviews with police, participants and witnesses, and the use of computer simulation. This is standard fare for these types of studies, and all we would point out here is that all such studies suffer from the same potential flaw. Namely, the speed estimates these studies derive for crashed vehicles are just that: Estimates. In the absence of measuring a vehicle’s speed with accurate speed detection equipment immediately prior to the crash (something not possible in the majority of cases), then researchers are inevitably left to rely on estimates of speed based on accident reconstruction techniques and interviews with police, participants and witnesses.
Where things get truly ridiculous in the Kloeden et al paper is their methodology for establishing the alleged average speed of the control vehicles not involved in crashes. The researchers endeavoured to measure the speed of vehicles on the same road location, at the same time of day, in the same weather conditions.
So far so good.
Here’s where things turn to crap: The total number of control vehicles, i.e. vehicles used to determine the alleged average speed on the studied sections of road was … 10.
No, that was not a typo – we did not leave out any zeroes. We repeat, the grand total of control vehicles used to determine the supposed average crash-free speed at each casualty crash location was a mere ten (10).
Keep in mind these were roads with speed limits of 80 km/h or more, within 100 km of Adelaide, and the overwhelming majority (92.2%) were sealed roads. We’re not talking rinky dink dirt roads in the middle of the outback, folks – the roads included in the analysis were the kinds of roads we could reasonably expect at least dozens, and more likely hundreds and in some cases thousands of vehicles to traverse in a single day. Yet the researchers chose a mere ten vehicles for each location to determine the alleged average speed of crash-free vehicles. Keep in mind these are the same researchers who belittled the research efforts of folks like Solomon, who used an average of 8,200+ control vehicles per studied section of road!
What a joke.
But wait, it gets worse.
Guess how the researchers determined the speed of the control vehicles?
By waiting until the control vehicles were within 200 metres, then pointing a laser speed detection device at them.
Excuse us while we face palm, folks.
Quick pop quiz #2:
You’re happily driving along a rural road, minding your own damn business, when suddenly you notice a sinister figure up ahead holding what suspiciously looks like a radar gun. What do you do?
In fact, when traveling on rural roads, many Australian drivers have learned to become suspicious of any vehicle or unexplained roadside presence ahead, before they see any evidence of speed detection equipment. Their instinctive response will be to slow down. Sure, the roadside entities involved may simply be tourists taking happy snaps or answering the call of Mama Nature, but suffice to say cars and their occupants generally don’t park and loiter in locations where there are no shops or no other obvious incentives to stop. But speed camera operators and laser gun-wielding police officers do.
So we have Kloeden and colleagues standing by the side of rural roads, pointing a laser device at oncoming cars, and happily presenting the resultant captured speeds as valid average crash-free speeds for that section of road.
Kloeden et al briefly acknowledged this issue, but then insisted “Even so, every effort was made to avoid alerting the drivers to the presence of speed measuring equipment.”
Despite the fact we are dealing with a confounding flaw that is a potential study-killer, Kloeden et al offer no further information on just what measures they took to avoid alerting drivers to their antics. Again, we are dealing with a confounding factor with the potential to completely obliterate this study’s already highly questionable results. If we are to believe the results of researchers who are claiming “even a 5 km/h reduction in the speed … would lead to a 31 per cent reduction in these casualty crashes”, then we need to be extremely confident that the detected speeds were highly accurate. It’s bad enough that we have to rely on estimates of the crashed vehicle speeds – but if the detected speeds of the control vehicles were out by even a small amount, then the results of this study are essentially worthless.
If some of the drivers noticed the radar-wielding Kloeden et al by the roadside in sufficient time to decelerate and wipe 5 km/h, 10 km/h or more off their recorded speeds, then this could have created a bias towards average lower speeds for the control vehicles. Especially given the pitifully low number of control vehicles involved, because the smaller a sample the greater the statistical impact of deviations from the norm within that sample.
But again, despite the critical importance of this issue, we are given little information other than a throwaway line that essentially amounts to a casual “don’t worry mate, we don’t reckon they saw us”.
Not good enough, guys.
But let’s for a moment be exceedingly generous, and assume the researchers did manage to wholly conceal themselves from oncoming motorists. To do this, they almost certainly had to have been obstructed from the motorist’s view. In other words, there would likely have been physical objects in between the researchers and the oncoming vehicles. If this were the case, then Kloeden et al need to re-read the instruction manual for their laser device. If that manual is worth a damn, it will point out that detecting the speed of oncoming vehicles with physical objects in the laser’s path or around corners where the laser’s path can be distorted by embankments, rock faces, trees, poles, etc. is not recommended because of the greatly increased likelihood of false readings (someone also needs to tell this to the hordes of unethical/ignorant Australian police officers who also use radar guns under these same questionable circumstances … )
And to top it all off, there’s a tradition here in Australia of alerting oncoming motorists to the presence of speed cameras and radars by flashing one’s headlights. In their 1997 paper that involved urban roads with 60 km/h speed limits, Kloeden et al acknowledged this and claimed they checked vehicles traveling in the opposite direction from their control vehicles to ensure they weren’t flashing their headlights. But in their 2001 paper, the researchers do not even mention this phenomenon let alone outline what measures, if any, they took to counteract it.
So what we are left with in Kloeden et al 2001 is a paper that:
-Not only ignored all non-casualty crashes in South Australia, but also deleted around 95% of the state’s casualty crashes, period.
-For the tiny remaining sample of casualty crashes, used a laughingly low number of control vehicles (10) to determine the supposed average speed of non-crash vehicles.
-Determined the average speed of this miniscule sample of control vehicles by pointing a laser device at members of a motoring public that has developed a deep distrust of people standing by the roadside pointing laser devices at them. In many motorists, this deep distrust causes one’s right foot to immediately leave the accelerator and instead place its weight on the brake pedal, causing their vehicle to slow down.
The Kloeden et al study, ladies and gentlemen, is an absolute joke, a complete waste of your taxpayer money.
But that’s still not the worst of it.
Not only was your tax money was given to a group of researchers who proceeded to produce a paper that would have failed to pass peer review in all but the most desperate journals, but … these same researchers then proceeded to make a series of utterly ridiculous recommendations based on their poorly contrived research.
Here are those recommendations, word for word:
“We therefore recommend that:
- The level of enforcement of speed limits in rural areas be increased.
- The tolerance allowed in the enforcement of rural speed limits be reduced or eliminated.
- All currently zoned 110 km/h undivided roads be rezoned to no more than 100 km/h.
- Speed limits be reduced where current limits are considerably greater than average travelling speeds and where there are frequently occurring Advisory Speed signs.
- After a period with stricter enforcement of rural area speed limits, consideration be given to changing the maximum speed limit to 80 km/h on all two lane rural roads, as is the practice on two lane rural roads in many States in the USA.
- The level of public awareness of the risk of involvement in a casualty crash associated with speeding be increased with the aim of developing a culture of compliance with speed limits, and support for strict limits, similar to that which has developed in relation to compliance with blood alcohol limits during recent decades.
- To assist with the preceding recommendation, we also recommend that the results of this study be widely publicised.”
Based on their very questionable results using their very questionable methodologies, Kloeden et al earnestly see no problem with issuing this most obnoxious and highly punitive series of recommendations. Based on nothing other than the results of their appalling study, Kloeden et al want Australian motorists to be policed even more unforgivingly and fined even more harshly!
They even put forth the ridiculous proposal that the speed limit on all two-lane rural roads be eventually reduced to 80 km/h, thereby ensuring that drivers traveling long distances will be far more likely to suffer accident-causing fatigue and distraction.
Imagine driving all the way from Melbourne to Adelaide, stuck at 80 km/h most of the way! Seriously, do these researchers ever drive interstate? Or do all their interstate trips take place in business class, courtesy of the same hapless taxpayers that fund their fanciful research?
Their recommendations take an especially Orwellian turn when they recommend that:
“The level of public awareness of the risk of involvement in a casualty crash associated with speeding be increased with the aim of developing a culture of compliance with speed limits, and support for strict limits, similar to that which has developed in relation to compliance with blood alcohol limits during recent decades.”
A “culture of compliance”? You mean using propaganda to influence people into thinking and behaving the way you want them to? The Big Brother-friendly Kloeden et al are calling for governments to step up their anti-speeding propaganda efforts (again, using your money) in order to convince you that the draconian measures they recommend are actually good for you. To encourage the implementation of this proposed brainwashing strategy, they cite the success of the anti-DUI campaign.
Trouble is, there’s a massive difference between the two. Anyone who has ever observed an intoxicated person would have little difficulty understanding why driving under the influence increases accident risk.
The anti-speed campaign, in contrast, is out and out bullshit. It is now 2017, and the best our governments can do to justify their revenue-raising speed enforcement capers is to mutter bullshit slogans, air bullshit advertisements, and defer to the bullshit non-peer reviewed research conducted by the university departments they fund. They ignore the research documenting reduced road deaths after the implementation of higher speed limits or removal of speed limits. They disgracefully remain silent on the fact that while speed camera revenue has gone up, so too has the road toll in most states. They claim “cameras save lives”, but when increasing speed camera revenue is correlated with an increase in the road toll, one can only conclude our governments are patently dishonest and corrupt entities with no intention of being truthful about road safety. Certainly not when such truthfulness will jeopardize their lucrative speed camera scam.
The seventh of Kloeden et al’s recommendations is truly a sight to behold:
- To assist with the preceding recommendation, we also recommend that the results of this study be widely publicised.”
Wow. Are these ‘researchers’ scientists or salesmen? In all our years of reading research papers, this is truly a first: A group of researchers, not just presenting their results, but actively encouraging others to pimp the hell out of them! We’re not sure whether these guys suffered delusions of grandeur, were starved for attention, or were talking up a call to arms on behalf of their government benefactors, but science is not the place for spruiking.
As Johnson and Pawar stated, some papers masquerading as speeding research are in fact far “more advocacy than science”, and the Kloeden et al paper is a textbook classic example.
But you know what? We’re happy to go along with recommendation #7, but we suspect it’s not in the manner Kloeden et al intended. Ladies and gentlemen, go forth, and publicize the hell out of the Kloeden et al paper. Seriously! Let everyone you know what a truly terrible study it is. Share with them the appalling methodologies Kloeden et al employed. Regale them with the draconian enforcement measures and Orwellian brainwashing strategies Kloeden et al recommended. Remind them that their hard-earned taxpayer dollars funded this nonsense. Remind them that while the rest of us are increasingly doing it tough and being told to tighten our belts, there are researchers at universities all around Australia being paid handsomely to churn out this brand of ultimately useless nonsense.
Tighter Controls on Those Who Truly Deserve It
Rather than place greater restrictions on predominantly law-abiding Australians, we propose that greater restrictions be placed upon researchers like those hailing from the taxpayer-funded RARU and MUARC units. Given their poor track record, it should be a requirement that, before any of their research can be cited in support of anything, it must be submitted for publication in an international (i.e. non-Australian) peer-reviewed journal. If the paper in question fails to pass the peer-review process, then the paper should be published on both an easily-accessible Government website and the relevant university’s website, with a highly visible disclaimer warning that the paper failed peer review, and a clear explanation of why. Any research not submitted for peer-reviewed publication should also be published on these sites, again with a clearly visible disclaimer warning that this research has not been peer reviewed, nor has it even been submitted for peer review. For the benefit of laypeople, an explanation of peer review and why it is important should also be part of these disclaimers. These explanations should be matter-of-fact and completely free of self-serving government/researcher spin.
Your Government Hates You
Australia is a federation of over-governed nanny states. Our federal and state governments are power-hungry, inherently corrupt entities comprised of individuals who care far more about rorting the system and milking whatever undeserved entitlements they can, rather than acting in the best interests of the public they allegedly represent.
One sad manifestation of the contempt with which Australian governments hold their constituents is the belief that the majority of motorists are too stupid to determine their own safe traveling speed. As a result of this alleged stupidity, people are told what speed they should travel on every section of road. Signs bearing speed limits are posted on roads, but the Australian government never explains to motorists the evidence base behind these speed limits. They are simply told to obey these limits, and that if they don’t and they are caught they will be issued with harsh financial penalties. These posted speed limits have declined over time – with the research of Kloeden et al often cited as justification in government reports and online propaganda – and there has also been a multiplication in the number of different speed limits. The resultant ‘bracket creep’ and confusion, of course, increases the number of motorists caught ‘speeding’, which in turn increases the already lavish sums of money that governments earn from this racket.
Those motorists who recognize this sham for what it is, and refuse to be stood over by dishonest individuals, whether of the underworld or badge-wearing variety, and hence refuse to pay their fines, will promptly be treated like criminals. They will be sent nasty letters, their fines will escalate, and, unless they contest the matter in court, their property will eventually be taken from them to recoup the amount they ‘owe’ the thug-like government in question.
Yep, when it comes to standing over easy targets, the police are pretty bloody formidable. They’ve even taken a leaf out of the book of the outlaw motorcycle gangs they purport to despise and set up specialized “enforcement” units dedicated to standing over those who do not pay their extortion fine payments.
To the law-abiding layperson, Australian law enforcement is steadily becoming an irrelevant farce. It revolves around using police forces as revenue raising agencies, empowering them to pick on easy targets for utter non-crimes such as exceeding non-evidence based speed limits by even small margins.
Meanwhile, individuals with long criminal histories, whose erratic behaviour has long been known to police, are allowed to continue their destructive carry-on, intercepted only after catastrophic events. Events that, if governments, our so-called ‘Justice’ departments, and our police forces were doing their jobs properly – instead of picking on law-abiding citizens for non-crimes – would never have occurred in the first instance.
If our governments, ‘Justice’ departments and police forces went after real criminals with the same tenacity they pursue drivers who refuse to pay their undeserved speeding fines, we suspect this country’s crime rate would plummet almost overnight.
The 85th Percentile
In contrast to the Australian approach, which is to contemptuously regard Joe and Jane Motorist as morons that need to be told exactly how fast to travel and fined harshly and harassed when they don’t do as told, the 85th Percentile paradigm utilizes a far different approach. Not only does this approach involve a far more benevolent attitude towards road users, it has a far stronger evidence base.
The 85th Percentile concept is based on the observation that most drivers are not reckless or suicidal and, left to their own devices will choose a safe speed of travel, regardless of the posted limit, one appropriate for the surrounding conditions and the type of road they are traveling on.
Given this observation, why not set the speed limit to match the speed the vast majority (around the 85% percentile, as observed in many studies) would safely drive at if left alone by overzealous speed enforcement entities?
On streets where low traveling speeds truly are necessary (e.g. narrow side streets that are often used as “rat runs” to avoid peak hour congestion on main roads) then traffic can be slowed through road engineering and design (curb bumpouts, speed humps, etc.). Note that, unlike speed cameras, these physical impediments have the effect of creating immediate reductions in speed. Speed cameras do nothing of the sort. Of course, installing physical speed impediments costs money, while speed cameras make money for our fiscally inept governments.
Sadly, there will always be reckless idiots with little respect for their own safety and that of others. That’s why, at SCS, we wholeheartedly support an increased police presence on the roads, but with one important caveat: This increased presence must be comprised of officers trained to look out for, and immediately act upon, truly dangerous road behaviours such as using mobile phones while driving, failing to move with the flow of traffic, reckless/aggressive and erratic driving, drink/drug driving, failing to allow sufficient room for cyclists, failure to give way/cutting across the path of other vehicles, tailgating and so on. These officers must be trained not to treat motorists like mobile piggy banks who are to be harassed and extorted for such trivialities as exceeding arbitrary speed limits by small margins. Malevolent police officers who abuse their position by engaging in such stupidity as booking motorists for traveling 1 km/h over the speed limit (see here and here for examples of such idiocy) should either have their employment terminated or be reassigned to menial office tasks, well away from the public.
As the US Traffic Engineering Handbook stated way back in 1965:
“Speed regulations and speed limits denote a restraint upon the freedom of the speed which he (the driver) desires to travel. Therefore limits or restraints should be imposed only to the extent that their use will facilitate traffic flow or decrease a traffic hazard.”[Bold emphasis hazard]
Speed limits and restraints should be imposed only when and where they will improve traffic flow and road safety – not as excuses to extort ever more money from the motoring public.
We think it’s fair to say most reasonable people fully understand the need for evidence-based safety measures, and would fully agree public roads are not the place for Formula One wanna-bes to test their driving skills (that’s what racetracks are for). As the Handbook further points out:
“Public acceptance is a prerequisite to effective public obedience to traffic regulations. If regulations are imposed only where and when they are necessary, the driver will more readily accept the need for them.”
To Australian governments: If you want to convince we the people that your lucrative anti-speeding regimes are truly about safety and not merely revenue-raising, then you need to present valid evidence that the speed limits being imposed are necessary and effective. Do not waste even more public money on propaganda and atrocious research to “create a culture of compliance”. Please refrain from wanking on about how the current system is “saving lives” when in fact the road toll in most states is increasing.
In other words, stop pissing in our ears and telling us it’s raining.
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A further note regarding the RTI study: In that study, data were gathered using a computer-sensor system, consisting of 16 magnetic loop pairs embedded in Indiana Highway 37 connected to an on-line digital computer system. This system measured mean traffic speeds and even allowed identification and speed measurement of crash-involved vehicles or the grouping of vehicles in which they had been traveling. Accidents occurring along the Highway were investigated by a team of professional accident investigators from Indiana University. Both the results of the accident investigation team and, when available, the computer-sensor system were used to determine pre-cash speeds.
As part of their critique of this study, Kloeden et al write:
“In order to test the reliability of the system, measures of pre-crash speed for a group of 36 crashes were obtained using both available methods. It was found that in a quarter of the cases the speed of the accident-involved vehicle or the platoon in which it had been travelling could be identified confidently from the computer output (a result which seemed to be regarded as an achievement rather than as a cause for misgivings about the quality of the data). Some information was retrievable for the remaining crashes, but it was not made clear how these less certain estimates were gained or treated.”[Bold emphasis added]
What the authors of the 1971 report actually wrote was that via correlation with the data from the professional investigators, in 9 of the 36 cases studied by means of the computer-sensor system the pre-crash speed of the vehicle or the “platoon” in which it was travelling was identified with “high confidence”.
And what did the authors do with the remaining 27 “less certain” estimates? We’re guessing that for the sake of consistency they discarded them and in those cases instead relied on the estimates from the professional research team. Indeed, that is what plain commonsense would dictate. Admittedly, the researchers don’t explicitly state this is what they did, but given their paper is free of the absurdities plaguing the Kloeden et al papers, we’re betting they took the commonsense approach.
One thing we can say for sure about the RTI study is that, all the way back in the 1960s, these US researchers had the wherewithal to employ a non-obtrusive speed detection system in their studies, in order to avoid influencing the speed behaviour of the motorists they were studying. Fast forward almost forty years, when research methodologies are supposed to have advanced in leaps and bounds, and we have Kloeden et al standing by the side of rural South Australian roads pointing laser devices at oncoming motorists.
And to add insult to injury, it is the former who have the gall to belittle the efforts of the former!