Autonomous Cars
When Will This Happen
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Self-driving cars are still a rarity and have largely been limited to testing facilities and other controlled conditions. But they are a seemingly inevitable next wave of technology that consumers and businesses will have to reckon with. Major automakers from Ford to Audi to Nissan have all been experimenting with autonomous vehicles, and many standard-issue models are now equipped with robotic skills including lane control and collision control and the ability to parallel-park themselves.
In March, Carlos Ghosn, CEO of the Nissan-Renault Alliance, said he expects the autonomous-driving revolution to have three phases -- a first wave emerging next year, followed by self-driving cars that can handle themselves on a highway by 2018 and then cars that can negotiate city driving by 2020.
Unlike Google's earlier self-driving Lexus models, which were standard SUVs rigged up with gear to help them get around autonomously, the bubble-shaped cars coming to Mountain View's public roads are prototypes designed by Google from scratch.
The new cars will use the same software that's installed in the Lexus vehicles. The Lexus fleet has driven around 1 million autonomous miles on the roads since the project started, Google said, and the results of all that driving have been used to tune up the driving skills of the new fleet.
All safety drivers in the new prototypes will have a steering wheel, accelerator pedal and brake pedal that will allow them to take control if needed. The speed of the cars will be capped at 25 miles per hour.
Google has been running these particular cars through the paces at its test facilities to make sure the software and sensors work properly. Their debut in Mountain View will mark the first time this fleet will venture out onto public roads. Google spokeswoman Jacquelyn Miller told CNET that over the past year, the team working on the new self-driving fleet has focused on three tasks:
1) Building the self-driving prototypes from scratch -- 25 of them to date. Google will roll out a few at a time starting this summer.
2) Continuing to refine the software by self-driving around 10,000 miles of city streets every week.
3) Developing the software's ability to handle "rare and weird situations" on the road -- what it refers to as the 0.001 percent of things that Google needs to be prepared for even if it has never seen that before in real-world driving.
The company will document the progress of its new self-driving public phase through the project's Google+ page. People who want to comment or ask questions about the project can share their thoughts on that page as well.
"We've had 20+ Lexus vehicles driving on Mountain View city streets for the last few years, but the arrival of our new self-driving vehicle prototypes marks the start of a new phase of our project," Miller told CNET. "We're proud of our driving record and development so far, and this new stage will help us understand what it really means to have self-driving vehicles in the world -- both how people in the community perceive and interact with them, and what the practical realities are for us in operating and maintaining them.
But Multiple Opinions, Conservative to Aggressive
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It sounds like we’re still going to be dealing with driverless cars, one way or another. How long do we have?
If you’re just talking about the time until we see some driverless vehicles on the road, probably not that long. Anthony Foxx, secretary of the U.S. Department of Transportation, went on the record in 2015 with the claim that “we’re going to see [fully autonomous cars] within five years,” though he allows that that “just means market availability.”
A more comprehensive timeline assembled by Recode suggests that by 2030, “Automakers will stop manufacturing cars that don’t have at least some highly autonomous features.”
It goes on to predict that by the middle of the 21st century, we’ll witness total fleet turnover, at which point virtually all vehicles on the road will be at least partially autonomous.
If that’s true, it’s possible that driving your own car will rapidly come to be seen as a dangerous affectation like smoking.
Three disruptive technologies will transform our transportation system.
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(Slate 16 June 2016)
It’s been a good year for electric cars. Tesla’s Model 3 has logged almost 400,000 preorders, GM is ramping up production of its 200-mile range Chevy Bolt, battery costs are plunging, and sales in the EU, China, and U.S. markets are up sharply from this time last year. And yet, some of the most respected analysts in government and the private sector have gone on record stating that EVs are too expensive and impractical to compete with the standard automobile—not just today, but for decades to come.
Exxon Mobil Corp., the Massachusetts Insitute of Technology, and the U.S. Department of Energy all agree that electric vehicles will remain a fringe technology for decades—until at least 2040. According to ExxonMobil’s crystal ball, electric cars will only comprise about 3 percent of the global automotive fleet by 2040. The U.S. Energy Information Administration is even more skeptical than Exxon Mobil, projecting that 2 percent of cars will be electric 25 years from now. MIT’s Sloan Automotive Laboratory only sees about 17 percent of new vehicles as plug-in EVs by 2050.
They’re wrong—for many reasons big and small. It’s easy to quibble with estimates of how fast battery prices will decline; or argue that they misunderstand the consumer appeal of electric cars. There is also a strong argument that manufacturers should be counting services rather than vehicles sold; and the role of policies pushing electric vehicles isn’t fully included in these numbers. (Case in point: Media reports say Norway is on the verge of announcing that it will phase out fossil fuel–powered cars by 2025.)
But these shortcomings, as significant as they may be, pale in comparison to the biggest hole in the logic of gloomy projections: The explosive synergies between three critical disruptions that are poised to revolutionize our transportation system sooner than most think. Together, the rise of self-driving cars; transportation service providers like Lyft and Uber; and electrification will transform the economics of getting places, the importance of these technologies in our daily lives, and the pace and pattern for deployment of innovative technologies. To understand each one of these technologies, you need to analyze them together.
Many modelers have missed this because they’ve done what they’ve always done: followed a formulaic approach. They add up yearly sales of new vehicles (in this case, electric), weigh that against how many other vehicles are junked and sold, and tally the result. And that’s worked all right in the past—all other things being equal, that formula should give you the relative percentage of electric cars on the world’s streets and their impact on future energy demand.
But different kinds of cars will have very different impacts on the technology mix of the future. Take the first disruptor: new mobility. Companies like Uber are already blowing up assumptions about how cars are utilized. Traditionally, cars sold in America sit parked more than 95 percent of the time. (Think about that—what other major capital investment sits idle 20 times more than it’s used? Commercial aircraft, for example, have much higher utilization—nearly 50 percent.) But companies like Uber and Lyft (or Bla Bla Car in France, or Kakao Taxi in Korea) have been able to leverage these massive, underutilized capital investments (privately owned cars) through smart logistics, good phones, apps, and ubiquitous connectivity. Interestingly, putting underutilized cars to work wasn’t Uber’s original plan, but the logic behind it is so compelling that both Uber and Lyft, which started off in very different places, co-evolved to embrace essentially the same business model—together with other new mobility companies around the world.
Better vehicle utilization is just the beginning. New technologies promise to propel this evolution even further by reducing costs and increasing operational efficiencies.
Two costs dominate driving: gasoline and the driver. The driver is by far more important, which is why autonomy (the second disruptor) is going to be so important. He or she represents a huge yearly outlay in operating expenditures costing even more than the vehicle itself. You can pick up a used Toyota Prius for $15,000, but it would cost more like twice that much to hire a person to drive it. So even if the add-on cost of the technology to make new vehicles autonomous ends up being relatively expensive (say $15,000 on top of the purchase price), it will rapidly pay for itself.
For practical purposes, this means that rideshare companies have all the incentive in the world to get humans out of the driver’s seat—and a robot into it. Of course, this is a very bad thing from the point of view of people making a living driving for these companies, but that’s hardly likely to outweigh the hard realities of business.
So there’s a strong link between the first two disruptors. With autonomy entering the picture, the most logical next step is for mobility services to move away from using private cars owned by individual drivers, to fleet vehicles owned by a company. Uber has already started to sound out automakers to find one willing to supply it with a fleet of autonomous cars. According to one study, this would reduce the cost of an Uber ride by as much as 80 percent per mile. And who wouldn’t want to save 80 percent—especially during a surge?
But the Ubers of the world won’t stop there. Once rideshare companies own fleets of autonomous vehicles that can be operated on an optimized schedule (since there won’t be a driver who needs to sleep and take coffee breaks), they will want to maximize the utilization of those vehicles and reduce their fuel costs. The easiest ways to do that are to run cars as often as possible and to put more people into a single car. We’re already seeing the latter, as Uber Pool and Lyft Line grow explosively (particularly in markets like China). By owning a fleet of vehicles, companies like Uber can optimize their design to make the carpooling experience significantly more comfortable, convenient, and attractive. The incentives are huge because every time Uber puts two people in a single car, they cut their capital costs by 50 percent. The company can incentivize pooling through lower cost or perhaps superior service.
Even after automation and carpooling, there’s one more piece of low-hanging fruit available to fleet operators: electrification. As batteries have gotten cheaper, EV ranges have increased and the economic logic of electric vehicles has steadily improved. With gasoline prices in early June at $2.34 a gallon, according to the Department of Energy’s eGallon, an electric vehicle is still about 50 percent cheaper to fuel than a gasoline vehicle. If you could save even 20 percent a year on fuel, electrification would seem like a pretty good idea. But when gasoline costs 200 percent as much as electricity for fuel, it’s way more than that—it’s a business imperative.
Right now, Uber and its competitors don’t own vehicles. They essentially rent the car and the driver. Today, that’s a great business model: Write apps, don’t own much capital, and you can be profitable very quickly. But somewhat counter intuitively, rideshare companies like Uber will make even more money owning capital assets—so long as they no longer have to rent an army of drivers.
Modelers have failed to appreciate the powerful synergies of electrification, automation, and fleet transportation services. The ineluctable economic logic that results from their interaction will be the story of 21st century transportation. Any company that fails to see the world through this lens does so at their own peril.
These economic forces, powerful as they are, will also be reinforced by government policy. Electrification, automation, and fleet services will likely have dramatic, positive consequences for greenhouse gas emissions, traffic safety, and the productivity of commuters. While there will be (serious) challenges related to job losses, cybersecurity and privacy, the net social-benefit logic will strongly encourage policymakers to help speed this transition along.
In short: Autonomous vehicles fleets are going to dominate the roads of the not-too-distant future; those vehicles are going to be electric; and each autonomous vehicle will probably be utilized 5 to 20 times as much as a standard automobile today. So even if only a small portion of total cars sold were electric, car-bot fleets would have a dramatically disproportionate effect on the percentage of transportation served by electric vehicles. For the purposes of forecasts, that’s what matters. Approximately 90 percent of a vehicle’s lifetime emissions are from its operation. If we can swap dirty gasoline with clean electricity, emissions from cars may cease to be a significant factor in human health and climate change.
No disrespect to Exxon Mobil, the Energy Information Administration, or MIT. This is just the kind of technological discontinuity that hits modelers in their blind spot. And that’s why they’ve got this one wrong.
Google's Plan to Eliminate Human Driving in 5 Years
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(Wired 19 May 2015)
GOOGLE’S ADORABLE SELF-DRIVING car prototype hits the road this summer, the tech giant announced last week. Real roads, in the real world. The car has no steering wheel or pedals, so it’s up to the computer to do all the driving.
As cool as this sounds, it isn’t a huge technological step forward. The goofy little cars use the same software controlling the Lexus and Toyota vehicles that have logged hundreds of thousands of autonomous miles, and Google’s spent the past year testing its prototypes on test tracks. And, in keeping with California law, there will be a human aboard, ready to take over (with a removable steering wheel, accelerator pedal, and brake pedal) if the something goes haywire.
What’s important here is Google’s commitment to its all-or-nothing approach, which contrasts with the steady-as-she-goes approach favored by automakers like Mercedes, Audi and Nissan.
Autonomous vehicles are coming. Make no mistake. But conventional automakers are rolling out features piecemeal, over the course of many years. Cars already have active safety features like automatic braking and lane departure warnings. In the next few years, expect cars to handle themselves on the highway, with more complicated urban driving to follow.
“We call it a revolution by evolution. We will take it step by step, and add more functionality, add more usefulness to the system,” says Thomas Ruchatz, Audi’s head of driver assistance systems and integrated safety. Full autonomy is “not going to happen just like that,” where from one day to the next “we can travel from our doorstep to our work and we don’t have a steering wheel in the car.”
Google thinks that’s exactly what’s going to happen. It isn’t messing around with anything less than a completely autonomous vehicle, one that reduces “driving” to little more than getting in, entering a destination, and enjoying the ride. This tech will just appear one day (though when that day will be remains to be seen), like Venus rolling in on a scallop shell, fully formed and beautiful.
In the past few years, Google has used about two dozen modified Lexus RX450h SUVs to drive nearly a million autonomous miles around Silicon Valley. It let select employees commute in self-driving cars on the highway. Its vehicles have been in 11 accidents in all that time, none of them serious, and none of them caused by Google. These days, the fleet is logging 10,000 miles a week, focusing on surface street driving, where variables like pedestrians, intersections, and cyclists make for a lot of complications. It expects to have a finished product by 2020.
There are three significant downsides to Google’s approach. First, the goal of delivering a car that only drives itself raises the difficulty bar. There’s no human backup, so the car had better be able to handle every situation it encounters. That’s what Google calls “the .001 percent of things that we need to be prepared for even if we’ve never seen them before in our real world driving.” And if dash cam videos teach us anything, it’s that our roads are crazy places. People jump onto highways. Cows fall out of trucks. Tsunamis strike and buildings explode.
The automakers have to deal with those same edge cases, and the human may not be of much help in a split second situation. But the timeline is different: Automakers acknowledge this problem, but they’re moving slowly and carefully. Google plans to have everything figured out in just a few years, which makes the challenge that much harder to overcome.
Second, it won’t have the benefit of a slow rollout to gradually deal with the big hurdles to self-driving cars: not just perfecting the technology, but dealing with regulatory issues, insurance questions, and consumer acceptance. Regulations are currently a mess, with some states making rules, others voting them down, and the feds basically stalling for time.
Recent studies show consumer interest in autonomous vehicles, but saying you may want a car that drives itself is not the same thing as buying one and trusting it with your life. It’s unclear how the insurance industry will react, though premiums could actually drop. Even if automakers do all the work figuring that stuff out, Google will miss out on years of sales.
And third, Google won’t reap the benefits of limited autonomy. You don’t need a car that drives itself 100 percent of the time to start cutting down on human error. Active safety systems now on the market are already saving lives. By insisting on landing the moonshot, you give up the upsides that come in the interim development stages. Namely, a bump in sales from consumers interested in cars even a bit safer than what else is on the market.
Google knows all this. And it has a strong counterargument.
“Ever since we started the Google self-driving car project,” team leader Chris Urmson wrote in a 2014 blog post, “we’ve been working toward the goal of vehicles that can shoulder the entire burden of driving.” Vehicles that take the human out of the equation altogether.
One of the trickiest—and little discussed—challenges facing automakers is how to handle the transition between computers and humans, particularly in an emergency. Building an autonomous system that requires occasional human control raises tricky questions, not the least of which is how you ensure the person at the wheel is alert and ready to take over. Audi’s testing has shown it takes an average of 3 to 7 seconds, and as long as 10, for a driver to snap to attention and take control, even when prompted by flashing lights and verbal warnings. At lot can can happen in 10 seconds, especially when a vehicle is moving more than 100 feet per second.
And as humans drive less and less, won’t we get worse at it? Doesn’t that make us a terrible backup system?
The deadly crash of Asiana Airlines Flight 214 at San Francisco International Airport in July 2013 highlights a lesson from the aviation industry. The airport’s glide scope indicator, which helps line up the plane for landing, wasn’t functioning, so the pilots were told to use visual approaches. The crew was experienced and skilled, but rarely flew the Boeing 777 manually, Bloomberg reported. The plane came in far too low and slow, hitting the seawall that separates the airport from the bay. The pilots “mismanaged the airplane’s descent,” the National Transportation Safety Board found.
Asiana, in turn, blamed badly designed software. “There were inconsistencies in the aircraft’s automation logic that led to the unexpected disabling of airspeed protection without adequate warning to the flight crew,” it said in a filing to the NTSB. “The low airspeed alerting system did not provide adequate time for recovery; and air traffic control instructions and procedures led to an excessive pilot workload during the final approach.”
Whatever happened, exactly, the crash that killed three Chinese teenage girls illustrates the difficulties that can arise when humans interact with complicated software designed to lighten their workload. Google wants nothing to do with that interaction. It believes computers can drive better than humans do, and it’s working full speed to hand over the controls completely, and as soon as possible.