The $1 Trillion Reason You Shouldn’t Be Allowed to Drive a Car
Earlier this year, the American Society of Civil Engineers (ASCE) released its quadrennial report card for America’s infrastructure, and the results are brutal. After examining infrastructure systems from aviation to wastewater, ASCE awarded the U.S. a D+, reflecting mediocre to poor conditions observed across nearly all areas. The highest grade given to any infrastructure category was B- (“good”) for solid waste management. America’s bridges, ports, public parks, and rail system all earned a C (“mediocre”) of one degree or another, while the rest of the 16 categories were given D’s (“poor”).
Among those categories are roads, which earned a solid D. If you spend any time driving — and data suggest that you do — then you already have a good idea why America’s roadways earned such a bad grade. “The infrastructure is in poor to fair condition and mostly below standard, with many elements approaching the end of their service life,” ASCE notes in its grading methodology. “A large portion of the system exhibits significant deterioration. Condition and capacity are of significant concern with strong risk of failure.”
Bad roads are not news to anyone — ASCE has been giving U.S. infrastructure bad grades for decades — but the problems created by these bad roads is getting worse. ASCE estimates that congestion on U.S. roadways costs the economy $101 billion each year in wasted time and fuel. Government estimates compiled by George Washington University indicate that drivers spend 34 hours each year stuck in congestion alone, while drivers in cities can spend up to 90 hours each year in traffic. This is about twice the waste observed in 1980, and left unchecked, it is only expected to get worse as the population increases and the nation continues to urbanize. A separate study by the Texas A&M Transportation Institute estimates that congestion cost people 5.5 billion hours in 2011 and burned 2.9 billion gallons of gasoline.
The Federal Highway Administration “estimates that $170 billion in capital investment would be needed on an annual basis to significantly improve conditions and performance,” of which about $91 billion is currently met by federal, state, and local governments. But to blame the roadways themselves, as bad as they are, for the congestion problem wouldn’t really be fair. Although roads and highways could use improvement and are in need of repair to remain functional, the real problem is that there are simply too many people driving too many cars. And to make it worse, as a whole, we’re all pretty bad drivers.
Once again, this is something that you probably have plenty of anecdotal evidence to support, but the argument is also backed by data. According to the National Highway Traffic Safety Administration (NHTSA), there were 5.5 million motor vehicle accidents involving 9.5 million vehicles in 2009. That’s nearly four out of every 100 vehicles registered in the U.S. And, unsurprisingly, the vast majority of these accidents are due to human, not mechanical, error.
Data on the root causes of congestion is harder to come by, but as much as we would like to blame construction zones for making us late to everything, traffic is largely a function of our aggregate driving behavior. If it’s not an accident that blocks a lane, it’s our own inability to carpool, drive in close formation with other cars, or merge in and out of traffic that slows us down the most.
And it’s not just time that we waste by being bad drivers. Tragically, we waste lives, as well. More than 33,000 people were killed in car accidents in 2009. This is nearly 10 percent below 2008 and among the lowest recorded since 1950, but still an intolerably high number. Moreover, 2.2 million people were injured in car accidents in 2009, and 240,000 of them were hospitalized for their injuries (NHSTA injury estimates go as high as 3.9 million). The major causes of these accidents were drunk driving, speeding, distractions, collisions with pedestrians and bicyclists, and failure to wear a seat belt — all an example of human error.
While quantifying the loss of life is a pretty arbitrary task, we can still at least ballpark the total economic cost of car crashes. According to the NHSTA, strictly financial costs like the destruction of property amount to $277 billion in costs each year, while social costs ring in at $594 billion.
“The economic cost of motor vehicle crashes in the U.S. is the equivalent of 1.9 percent of the $14.96 trillion Gross Domestic Product,” the NHSTA says. That’s nearly $900 billion. “Factors contributing to the price tag include productivity losses, property damage, medical and rehabilitation costs, congestion costs, legal and court costs, emergency services, insurance administration costs, and the costs to employers, among others. Overall, nearly 75 percent of these costs are paid through taxes, insurance premiums, and congestion related costs such as travel delay, excess fuel consumption, and increased environmental impacts. These costs, borne by society rather than individual crash victims, totaled over $200 billion.”
The obvious followup question is this: What can do we do about this? ASCE’s diagnosis of road conditions suggests that we should invest more in the infrastructure itself. Investing in road repairs and bridge maintenance is critical, but it’s not a true solution. Again, the real problem is not that the roads are bad — the real problem is that we’re not good enough at driving to avoid getting into accidents, let alone to drive efficiently. Statistically, we are a danger to society when we are behind the wheel of a car.
This means that any real solution to the problem will have to do with people, specifically with people as operators of motor vehicles.
Fortunately, and not too surprisingly, humans are not the best drivers on the planet. At least, it doesn’t look like they will be for long. Thanks to the efforts of researchers and engineers from around the world, cars themselves are rapidly catching up to humans as drivers, and in many cases have already surpassed us.
Dozens, if not hundreds, of teams of researchers and engineers around the world are working on self-driving cars, but Google is probably the most visible. In the past few years, Google has demonstrated that a self-driving car can perform in most real-world driving situations. Moreover, because a car can drive itself more reliably, precisely, and efficiently than a human can, we could get much more actual transportation out of our existing road network and with much fewer roads.
According to data compiled by business consultant Chunka Mui, mass adoption of self-driving cars could reduce most driving-related costs by 90 percent. That’s 90 percent fewer accidents, 90 percent less congestion, and a 90 percent reduction in the overall number of cars on the road.
“Our car is driving more smoothly and more safely than our trained professional drivers,” said Chris Urmson, who heads the self-driving car project at Google, at a robotics conference in 2013, according to the MIT Technology Review.
Granted, there are a thousand things standing in the way of mass adoption of self-driving cars. Not only does the technology need more time, but regulators, businesses, and the public needs more time, as well. According to Mui, there’s at least $2 trillion in revenue each year generated by the auto industry or by industries somehow related to cars. Much of that revenue reflects large industrial institutions ranging from car manufacturers to insurance agencies, both of which would rather see slow, incremental change.
Even if industry were on board (and many major car companies are working on some form of self-driving technology), consumers will have to trust and embrace the technology. This could be challenging in the U.S., where car ownership has as much cultural significance as it does economic significance.
But the problem — the enormous cost of human error in driving — could weather the opposition. A 90 percent reduction in driving-related costs is an enormous incentive for consumers to make a purchasing decision, should a reasonable one be presented. With enough demand-side pull, and with sufficient supply-side push, we could see self driving cars sooner rather than later.
Here’s Dave Ferguson, who leads the machine learning and computer vision teams for Google’s self-driving car project, describing the vision.