Tag Archives: accidents

Most traffic deaths are from driving too slow

About 40,100 Americans lose their lives to traffic accidents every year. About 10,000 of these losses involve alcohol, and about the same number involve pedestrians, but far more people have their lives sucked away by waiting in traffic, IMHO. Hours are spent staring at a light, hoping it will change, or slowly plodding between destinations with their minds near blank. This slow loss of life is as real as the accidental type, but less dramatic.

Consider that Americans drive about 3.2 trillion miles each year. I’ll assume an average speed of 30 mph (the average speed registered on my car is 29 mph). Considering only the drivers of these vehicles, I calculate 133 billion man-hours of driving per year; that’s 15.2 million man-years or 217,000 man-lifetimes. If people were to drive a little faster, perhaps 10% faster, some 22,000 man lifetimes would be saved per year in time wasted. The simple change of raising the maximum highway speed to 80 mph from 70, I’d expect, would save half this, maybe 10,000 lifetimes. There would likely be some more accidental deaths, but not more accidents. Tiredness is a big part of highway accidents, as is highway congestion. Faster speeds decreases both, decreasing the number of accidents, but one expects there will be an increase in the deadliness of the accidents.

Highway deaths for the years before and after Nov. 1995. Most states raised speeds, but some left them unchanged.

Highway deaths for the years before and after speed limit were relaxed in Nov. 1995. At that time most states raised their speed limits, but some did not, leaving them at 65 rural, 55 urban; a few states were not included in this study because they made minor changes.

A counter to this expectation comes from the German Autobahn, the fastest highway in the world with sections that have no speed limit. German safety records show that there are far fewer accidents per km on the Autobahn, and that the fatality rate per km is about 1/3 that on other stretches of highway. This is about 1/2 the rate on US highways (see safety comparison). For a more conservative comparison, we could turn to the US experience of 1995. Before November 1995, the US federal government limited urban highway speeds to 55 mph, with 65 mph allowed only on rural stretches. When these limits were removed, several states left the speed limits in place, but many others raised their urban speed limits to 65 mph, and raised rural limits to 70 mph. Some western states went further and raised rural speed limits to 75 mph. The effect of these changes is seen on the graph above, copied from the Traffic Operations safety laboratory report. Depending on how you analyze the data, there was either a 2% jump (institute of highway safety) in highway deaths or perhaps a 5% jump. These numbers translate to a 3 or 6% jump because the states that did not raise speeds saw a 1% drop in death rates. Based on a 6% increase, I’d expect higher highway speed limits would cost some 2400 additional lives. To me, even this seems worthwhile when balanced against 10,000 lives lost to the life-sucking destruction of slow driving.

Texas has begun raising speed limits. Texans seem happy.

Texas has begun raising speed limits. So far, Texans seem happy.

There are several new technologies that could reduce automotive deaths at high speeds. One thought is to only allow high-speed driving for people who pass a high-speed test, or only for certified cars with passengers who are wearing a 5-point harness, or only on roads. More relevant to my opinion is only on roads with adequate walk-paths — many deaths involve pedestrians. Yet another thought; auto-driving cars (with hydrogen power?). Computer-aided drivers can have split second reaction times, and can be fitted with infra-red “eyes” that see through fog, or sense the motion of a warm object (pedestrian) behind an obstruction. The ability of computer systems to use this data is limited currently, but it is sure to improve.

I thought some math might be in order. The automotive current that is carried by a highway, cars/hour, can be shown to equal to the speed of the average vehicle multiplied by the number of lanes divided by the average distance between vehicles. C = v L/ d.

At low congestion, the average driving speed, v remains constant as cars enter and leave the highway. Adding cars only affects the average distance between cars, d. At some point, around rush hour, so many vehicles enter the highway that d shrinks to a distance where drivers become uncomfortable; that’s about d = 3 car lengths, I’d guess. People begin to slow down, and pretty soon you get a traffic jam — a slow-moving parking lot where you get less flow with more vehicles. This jam will last for the entirety of rush hour. One of the nice things about auto-drive cars is that they don’t get nervous, even at 2 car lengths or less at 70 mph. The computer is confident that it will brake as soon as the car in front of it brakes, maintaining a safe speed and distance where people will not. This is a big safety advantage for all vehicles on the road.

I should mention that automobile death rates vary widely between different states (see here), and even more widely between different countries. Here is some data. If you think some country’s drivers are crazy, you should know that many of the countries with bad reputations (Italy, Ireland… ) have highway death rates that are lower than ours. In other countries, in Africa and the mid-east death rates per car or mile driven are 10x, 100x, or 1000x higher than in the US. The countries have few cars and lots of people who walk down the road drunk or stoned. Related to this, I’ve noticed that old people are not bad drivers, but they drive on narrow country roads where people walk and accidents are common.

Robert Buxbaum, June 6, 2018.

Statistics of death and taxes — death on tax day

Strange as it seems, Americans tend to die in road accidents on tax-day. This deadly day is April 15 most years, but on some years April 15th falls out on a weekend and the fatal tax day shifts to April 16 or 17. Whatever weekday it is, about 8% more people die on the road on tax day than on the same weekday a week earlier or a week later; data courtesy of the US highway safety bureau and two statisticians, Redelmeier and Yarnell, 2014.

Forest plot of individuals in fatal road crashes over 30 years. X-axis shows relative increase in risk on tax days compared to control days expressed as odds ratio. Y-axis denotes subgroup (results for full cohort in final row). Column data are counts of individuals in crashes. Analytic results expressed with 95% confidence intervals setting control days as referent. Results show increased risk on tax day for full cohort, similar increase for 25 of 27 subgroups, and all confidence intervals overlapping main analysis. Recall that odds ratios are reliable estimates of relative risk when event rates are low from an individual driver’s perspective.

Forest plot of individuals in fatal road crashes for the 30 years to 2008  on US highways (Redelmeier and Yarnell, 2014). X-axis shows relative increase in risk on tax days compared to control days expressed as odds ratio. Y-axis denotes subgroup (results for full cohort in final row). Column data are counts of individuals in crashes (there are twice as many control days as tax days). Analytic results are 95% confidence intervals based on control days as referent. Dividing the experimental subjects into groups is a key trick of experimental design.

To confirm that the relation isn’t a fluke, the result of well-timed ice storms or football games, the traffic death data was down into subgroups by time, age, region etc– see figure. Each groups showed more deaths than on the average of the day a week before and after.

The cause appears unrelated to paying the tax bill, as such. The increase is near equal for men and women; with alcohol and without, and for those over 18 and under (presumably those under 18 don’t pay taxes). The death increase isn’t concentrated at midnight either, as might be expected if the cause were people rushing to the post office. The consistency through all groups suggests this is not a quirk of non-normal data, nor a fluke but a direct result of  tax-day itself.Redelmeier and Yarnell suggest that stress — the stress of thinking of taxes — is the cause.

Though stress seems a plausible explanation, I’d like to see if other stress-related deaths are more common on tax day — heart attack or stroke. I have not done this, I’m sorry to say, and neither have they. General US death data is not tabulated day by day. I’ve done a quick study of Canadian tax-day deaths though (unpublished) and I’ve found that, for Canadians, Canadian tax day is even more deadly than US tax day is for Americans. Perhaps heart attack and stroke data is available day by day in Canada (?).

Robert Buxbaum, December 12, 2014. I write about all sorts of stuff. Here’s my suggested, low stress income tax structure, and a way to reduce/ eliminate income taxes: tariffs– they worked till the Civil war. Here’s my thought on why old people have more fatal car accidents per mile driven.