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The Quest to Build the Driverless Car - and How It Will Reshape Our World

By Lawrence D. Burns with Christopher Shulgan

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When Burns moved to the Columbia U think tank (see below) he initiated research project to consider the implications of transport ind disrupted by three separate but inter-related factors - shared use vehicles,powered by electric motors, and driven autonomously.

2011 calculation that deployment of such an integrated system wd reduce the annual cost of travel in US by $4 trillion. For the individual, it wd reduce the direct and indirect (out-of-pocket and time costs) costs from $1.50 a mile to $0.25 a mile.

Better mobility for more people at a lower cost.

Will change the business model for car companies. Today, the average nett income per vehicle (everything except pickups) is between $1000 and $5000. That's selling millions of vehicles to millions of different customers. The future model will be running huge fleets of self-driving taxis earning $0.10 per mile for a 300,000 mile lifetime - ie a lifetime profit of $30,000.

Dave Hall famously built an amplifier at age of four. At college he patented a tachomemter, which gave him enough income that he didn't need to get a job after graduating. Instead he set up his own workshop. In 1979 he started manufacturing his own subwoofer invention,which finaced his battlebot hobby. He was a LIDAR pioneer, figuring out how to cram 64 lasers on to a single device. More importantly, his LIDAR spun, producing a 360°, dimensional picture of environment.

Hall hired Anthony Levandowski towork for his LIDAR company, Veladyne. AL had been in the first DARPA trial with a riderless motorbike called Ghost Rider (which was an ignominiuos failure - the operators forgot to turn on its gyroscope, and GR fell over ob the start line).

Sebastian Thrun cuthis teeth on a robot called Groundhog, which mapped abandoned mines in Pennsylvania for companies wanting to reopen them. In 1998 he built a robot docent for Washington's Smithsonian Museum. Solved navigation problems by creating a room map by sending robot around at night when place empty, and solved the don't-knock-a-child-over problem by coding it to interpret any change to the map as a human, and to stop and wait for it to move away.

Thrun ran the Stanford U team which won the second DARPA challenge (and a $2 million dollar prize) with Stanley, a converted 2004 VW Toureg. During their prep, they had attached multiple cameras on the roof to let them recap what had happened whenever something went wrong. Realized that it was interesting just going through the pics, so Thrun assigned an undergrad, Joakim Arfvidsson, to create a program to stich all the clips together to make seamless view.

Levandowski joined this team in 2007. He was responsible for creating a demo that would sell the startup to VCs. He hired a fleet of rentals (cheap if you rented by the month), and hired a fleet of drivers off Craigslist. Took two weeks to film all of San Francisco. Google bought the startup and team for an undisclosed sum, heading off VCs who were competing to invest.

Gm Autonomy concept car 2002 Auto Show - a skateboard with fuel cell powering 4 individual wheel motors. Everything below the platform, which allowed multiple cabins to be dropped on top.

GM, Ford etc sit on top of an 'intgrated auto industry'. They manage a supply chain of parts suppliers to assemble finished vehicle. In 2005 Burns and his boss, Rick Wagoner, called to the GM Vehicle Assessment Center. This was where GM disassembled their competitors' cars, right down to the last nut and bolt. At this visit, they were shown 3 vehicles: a Chevy Malibu, which was broken down into about 10,000 parts, a Toyota Prius hybrid, which had even more parts (bc double up systems), and finally, GM's electric car, the E-Flex. This had less than 1000 parts.

This was an epiphany, bc it meant the car was way easier to manufacture. Not only did it have a tenth the number of parts, it had a lot fewer moving parts. This meant the door was open for a lot more car companies, who wd not need GM's knowledge of organizing a huge supply chain.

And further, the crucial expertise was not going to be managing the hardware, but the software. Cars would be designed, engineered and controlled by programmers, not metal-bashers.

Analagous situation to the 1980's, when IBM outsourced the chips and the programming of PCs, not realizing that that was where the value lay.

Larry Page had to browbeat Sebastian Thrum into making AVs. Despite his experience with the successful DARPA challenges, Thrum considered normal street AV driving was impossible. But Page said "I've thought about this. Give me a technical reason why it can't be done. Not a societla reason. A technical reason."

Thrum reminded Page that he was the world authority on AVs, and if he said it was impossible, he should know. But he couldn't come up with a technical answer, and so, Oct 2008, first assembled a team to address the challenge. Chris Urmson charged with developing the software. Levandowski to run the hardware and Mike Montemerlo to develop the maps. The project was to be called Chaffeur.

The maps were the key for the cars to locate themselves in the world. First, cars equipped with LIDAR and cameras would drive the same streets multiple times day and night. By compring things that changed position between scans with those which didn't, the software created a list of staionery objects (curb edges, buildings, street signs, telephone poles etc). Then, when AV navigated same territory, it wd scan its current surroundings and match it with its database of maps. This gave a very precise location with a margin of error of two inches.

Basic navigation was straightforward. The team ran a demo obstacle cource which they put their AV through, then challenged the fifty Google execs watching to beat the time. None could.

From there, the first step was teaching robot to recognize objects. So thousands of images of pedestrians, wheelchairs, cats and dogs, skateboarders, balls etc. The most challenging was a traffic cop directing traffic, with their multiple idiosyncratic ways of signalling.

Then they had to develop a behavioural engine - predicting what allthose objects cd potentially do, including whatother vehicles might do. The trickiest one here was guessing whether a cyclist hitting an intersection on yellow light wd run the red, and so AV would have wait, even though it had a green light.

When Google tried to interest Detroit in its AVs, the execs were dismissive - "People like to drive" and "People's self-image is tied up with their car". But these old white guys had missed the change. Kids now were more interested in buying the latest iPhone than in having a cool car.

Zimbabwe's casual transport 'system' - if you wanted a ride you just stuck out an arm and the nearest car with an empty seat would pull over. You just paid a small sum as gas money.

An American driver's cost of car. The AA annually estimates the out-of-pocket cost - depreciation, fuel, insurance, maintenance and finance. They estimated that thetypical cost was $0.65 per mile, incl parking. Burns then calculated the cost of the time spent driving. (Simply divided av wage of $24 an hr by the av driving speed, which was roughly 28 mph). That cost came out at another $0.85 per mile, so total cost of owning an operating a car was about $1.50 per mile (in 2011). So Americans spent around $4.5 trillion per year driving.

Burns' team ran another set of calculations to figure out how many AVs wd be needed. Then ran multiple iterations with different scenarios, and kept coming up with the same numbers. You needed just 15% of vehicles currently in a town or city to simultaneously achieve the three vital goals - high fleet utilization, low empty miles (between fares) and fast response times. And to cover rush hour surges you wd need a maximum of another 5%.

Driving costs wd be dramatically lower. The car cd be built for lot less than $10,000, excluding the self-driving system. That, once in mass-production, will cost less than $5000. Based on 250,000 miles travel (which is what most taxis do), the cost wd be around $0.05 per mile. Cost of electricity to power it, $0.01 per mile. Maintenace costs set at $0.05 to allow for cost of replacing batteries. Insurance at $0.02 per mile bc expect very few accidents. And another $0.02 for parking and financing. Total cost $0.15 per mile v $1.50 for ICE car today.

So even though the car companies were blind to the coming disruption, Google could see this as a massive business opportunity. Conservatively estimating that AVs cd capture 10% of the 3000 billion miles driven each year in Amerca. If you charged $0.10 margin over cost, you wd still only be charging $0.25 a mile, but your profit would be $30 billion pa.

Google found a regulatory loophole - low speed vehicles. A LSV can weigh up to 3000 lbs and have a top speed of 25mph. So they built 100 prototypes called Firefly, which, sensationally, had no steering wheel or brake or gas pedals -just an ON and OFF button.

For Detroit, the game changed at beginning 2015. Insiders had been quietly challenging the petrolhead mentality of "Everybody likes to drive" (except nobody syays they enjoy their commute) and "people's self-image is tied up with their cars, particularly young guys" (except that today's youth would rather spend their money on a better cellphone than a car, and are quite happy to use Uber to get around).

The attention grabber was Uber swooping in and poaching virtually thewhole staff of the National Robotics Engineering Center at Carnegie Mellon. It got a lot of attention from Detroit bc basically an endorsement of Google's AV concept and a belief in first-mover advantage. The coup set off a stampede, as auto makers realized that the AVs were coming very soon, and that their business model was going to be overwhelmed.

Owning a car is inflexible - people buy them for "the occasional but imperitive" use. They'll buy a pickup or an SUV so that they can carry large loads once or twice a year, but then is massively over-engineered and equipped for what they usually use it for. So car fleets would offer renters small two-seaters for most of the time, but also have a small fleet of bigger, special purpose vehicles to cope with that occasional use.

Tesla used Mobileye to run its driver-assist system. But Mobileye's makers, an Israeli firm, repeatedly told tesla it was wrong to call it an Autopilot, bc it was designed purely for use on freeways to monitor other vehicles travelling in the same direction. It simply wasn't designed to detect another vehicle crossing the road at right angles (which is how the tesla driver in Florida died)



The car, notes Lawrence D. Burns in his book Autonomy, is terribly inefficient. The internal combustion engine converts less than a third of a gallon of gasoline into actual kinetic energy - the rest is wasted as heat and sound. And most of the kinetic energy goes to simply moving the (increasingly large) car itself. Only about 5 percent of the gasoline energy is used to move the driver. Most people drive to work alone, in cars with too much capacity and engine power for that purpose. Then there's the fact that most cars sit unused 95 percent of the time. Not to mention the societal costs in death and injuries, the environmental costs of the cars themselves, and the infrastructure supporting all this inefficiency. If this sounds insane, as one observer put it, Burns reports that he couldn't agree more.

This might read like the buzzkill PowerPoint of some progressive transportation think tank analyst. But Burns was, for many years, a vice president at General Motors, whose workforce, he points out, once exceeded the combined population of Delaware and Nevada and whose fortunes were intrinsically yoked to the country at large.

Burns did eventually go to work for a think tank - he's the director of Columbia University's Program on Sustainable Mobility at the Earth Institute - but for much of his life, this Detroit-born-and-bred engineer, schooled at a General Motors-run college before taking his first job with the company, worked firmly within the system, crafting massive 10-year plans and optimizing production processes. But, he admits, he never felt like a car guy. He was, at heart, a mobility guy, and mobility guys did not necessarily think that single-occupant-driven SUVs (still the bread and butter of the auto industry) were the best way to move the most people around most safely and most efficiently.

The story he sets out to tell in Autonomy, aided by the writer Christopher Shulgan, is one of increasing disenchantment with the status quo in Detroit. The car, after all, had barely changed since the Model T: Gas-fueled, run by an internal-combustion engine, rolling on four rubber tires, with the passengers protected by a windshield and four doors. Sure, there was plenty of incremental innovation, but the car was an entrenched technology stubborn to change. However, an epiphany was to come - from the desert where teams of roboticists were competing to come up with a way to reduce the number of soldiers dying while driving Humvees. The challenge from the Defense Advanced Research Projects Agency (DARPA) had rival groups working to get their driverless vehicles across the finish line on a course in the Mojave.

Burns later agreed to sponsor a team from Carnegie Mellon as it embarked on the biggest challenge yet: piloting an autonomous vehicle through an urban environment. This is not exactly the realm of 'The Right Stuff.' Here we have slow-moving cars bumbling through parking lots and patiently navigating four-way intersections. But you can sense the excitement in Burns, an engineer at heart, as the team works through the night in unheated trailers in Pittsburgh winters on what would eventually be the winning entry: a modified Chevy Tahoe, named Boss, that successfully completed the 60-mile course.

For Burns, this was more than a proof of concept, it was a nascent revolution, the sort of mobility disruption he hoped to see: He longed not only to take the internal combustion engine out of the vehicle but to remove the driver. The concept was launched as the Internet sharing economy took off. Now humans could be freed from parking - cars would do it themselves. And freed from driving - a driverless car ordered online would come pick you up and take you wherever you wanted to go. But, as Burns tells it, the industrial story is a familiar one: brave innovators running up against organization men. Unlike the 'move fast and break things' ethos of Silicon Valley, Detroit took years to move from concept to prototype. And the car guys mostly just didn't get why people would not want to drive. During the Urban Challenge, Burns notes, Google sent a 'planeload' of senior executives; GM, by contrast, sent only him. In Silicon Valley, the human driver was regarded as a bug - not a feature - in a car. For decades, the car guys in Detroit had sold cars on the promise that driving was freedom. Now the fear was that robot cars were the beginning of the end of humans. An ad for the 2011 Dodge Charger shows the human-driven vehicle picking up speed as a voiceover intones: "Leader of the human resistance."

The ad, presumably, was at least partially tongue in cheek, but it does illuminate a shortcoming of Autonomy. The book is a passionately argued, you-were-there account of the birth and rise of the autonomous vehicle from an authoritative Detroit voice. Burns, a technological utopianist (and one of the first people to get a cochlear ear implant), makes a number of compelling arguments for why smaller, self-piloted, shared vehicles make sense. But we don't hear much about that other great engine of the car business: consumer desire. Do people want to be driven? Corporations can be intransigent, for sure, but so can consumers. Seat belts in cars, for example, were introduced almost 70 years ago, but they were quickly abandoned because consumers resisted them, and it took many decades for this standard safety feature of today to gain acceptance. As with seat belts, it may take more than simple availability for consumers to adopt the technology.

And the engineering hurdles are signficant. Making cars drive themselves is, as Uber's co-founder Travis Kalanick once put it, a “hard problem.” Human transportation, however, can be a wicked problem. Fixing one problem can often lead to unintended others (Uber, which was posited as a way to smooth traffic by reducing car ownership, has arguably taken people off public transit in New York and helped worsen congestion.) And even the much-publicized early fatalities attributed to autonomous vehicles - two Tesla drivers using autopilot and a pedestrian struck by an Uber test vehicle - may have been results of programming decisions made by humans. A larger question, not much discussed in Autonomy, is how much risk we are willing to accept to have autonomous vehicles. What role should ethics have in the programming: Do we prize safety over speed and efficiency? And who should be the ultimate arbiters of those decisions?

Burns is right to envision a better future with computer-assisted driving (simply eliminating the possibility of drunken driving would save thousands of lives in the United States alone). But like a parent handing the car keys to a newly licensed teenager, relinquishing autonomy to computers - which also seems inevitable — will come with a curious mixture of hope, fear, regret and more than a few mishaps. "Enjoy the ride," Burns offers as his final words - but do buckle up.


How has autonomy become a commonplace term in our conversations? It seems only a short time ago that autonomous vehicles seemed futuristic and a little far-fetched, doesn't it? In Autonomy: The Quest to Build the Driverless Car… and How It Will Reshape Our World, Lawrence D. Burns describes a transportation future where we safely and conveniently use autonomous vehicles to take us where we want to go.

How have we come so close to this reality of on-demand transportation autonomy? In Autonomy, Burns narrates how robotics teams have taken hundreds of thousands of steps to train self-driving cars to react to the same obstacles to which human drivers react. And the story of that technological roadtrip is fascinating - especially to those of us who have heard pieces of the autonomy story but didn't understand the ramifications of the self-driving Big Picture.

The book points to a future in which our trips will primarily take place in a 2-seater electric vehicle (EV) hailed through a car-sharing company. As users, we'll pay a monthly subscription fee in exchange for on-demand use of a company vehicle for a certain number of miles per month. Autonomy helps us to understand this likely future reality by taking us back to the beginning of robotic transportation research.

The book, however, is not an encyclopedic compilation of dry sequential facts. Burns' career spanned head of research and development at General Motors to consultant at Google. Likely not a confident writer himself, Burns was wise: he brought on a ghostwriter, Christopher Shulgan. As a result, the chapters unfold as stories with a mystery genre-like tone.

For example, Chapter One is the story of the Defense Advanced Research Agency (DARPA) challenge to stage a race for robot cars across the Mojave Desert. The adventures of the robot named Sandstorm are unveiled in real time and with a sense of suspense, urgency, and wonder - will it win? Had its team anticipated all technology glitches?

Of course, having famous names like Google co-founders Larry Page and Sergey Brin sprinkled throughout the chapters doesn't hurt, either. ("Larry's always been a robotics enthusiast," one of the team noted.) The authors blend dialogue from interviews; infuse historical contexts (i.e. the importance of drone imagery from Iraq and Afghan territories); trace a cast of unlikely, contradictory, and often combative tech team characters; and, unveil a play-by-play of robot races that reads like a whodunit.

When our protagonists (spoiler alert) fail to win the DARPA challenge, all is not lost. A second race, which, like the first, required publishing for the rest of the robotics community the secrets of all competitor's approaches, brings in new characters like Sebastian Thrun from the Stanford AI Laboratory. His team heightens tensions among the original Red Team of Red Whittaker, Chris Urmson, and others - some of whom were drawn from a graduate-level seminar class called Mobile Robot Development.

Instead of Sandstorm's electrical motor and lever that pushed against the gas pedal, the new entry, HIghlander, has a throttle that was controlled electronically through a computer system. With less margin of error, HIghlander was becoming a better robot driver.

Sure, robot cars encountered obstacles they didn't understand, like rolling over on a test track when sandbanks resembled a computer scenario that called for acceleration into a curve. When the robot would encounter something it couldn't handle during research phases, someone on the team would code a fix. As the process repeated itself dozens, and eventually hundreds of times, the robot became sophisticated enough that it began to teach itself.

Robotics had been seen as novelties, curiosities that had little effect on anyone's day-to-day lives. Then the 3rd race, the 2006 DARPA Urban Challenge, sought robots that could navigate the chaotic urban environments of Iraq or Afghanistan - traversing 60 miles in 6 hours while obeying the rules of the California Driver Handbook. As part of that Challenge, Dave Hall became fascinated with LIDAR's potential to create a 3-dimensional scan of the world so that the robot could detect oncoming vehicles in all directions. And Anthony Levandowski - later to become well-known in 2017 in a lawsuit between Waymo and Uber - was selling LIDAR to as many teams as he could. Meanwhile, Thrun and Levandowski sold their VueTool technology to Google to accelerate the Street View project.

While Street View was in development, Urmson and Slesky were constructing situations that would wreak havoc on their vehicles computer algorithms - situations unlikely to happen in real life, which resulted in a robot that could drive in traffic at the speeds that were commonplace on public roads.

Problems did stymie continual forward progress in autonomous vehicles. As GM tried to separate itself from its health care obligations and with the specter of bankruptcy looming, company research into autonomy fell by the wayside. Ideas to design an autonomous vehicle based on the Segway idea seemed, well, silly to audiences. The idea that self-driving cars were a near-term possibility seemed too idealistic - that is, until Larry Page told Thrun that he should work on self-driving cars. With the budgetary backing that Google could provide, Thrun hired a team of about 12 engineers to create an autonomous vehicle that could successfully navigate 10 drives totaling about 1000 miles. These routes would duplicate the driving experiences of most any California street.

Using the Google Street View service, which the Autonomy authors describe as "a cartographic achievement unmatched since the days of Vasco de Gama and Magellan" (p. 173), the team had access to artificial intelligence and computer-vision software. Their autonomous vehicle, named Chauffeur, had an ability to locate itself in the world, conduct a similar scan of the area around it, and match its current surroundings with the list of landmarks in its 3-D maps. How did it work? The car would:

compare its preexisting list of stationary objects with the objects around it to discern which objects were likely to move
draw upon the 3-D maps, which could also help the vehicle discern the dotted or solid lines in the middle of the road
determine tricky but important parts of the world around it - like traffic lights (p. 174)

Optimism permeates Autonomy. When Google executives are invited to run the same route as Chauffeur but faster than the robot, not one exec succeeds. The authors exclaim that the team was creating a vehicle that could drive not only as well as a human being - but better than one. Faster, sure. But more importantly, more safely, with less of a tendency to get distracted or confused.

These tests were conducted on public roads, which shocked America when newspaper headlines captured the pilot project. Still, the authors insist that the Google car had sensors all around it. It knew what was happening ahead, as well as to the right and the left, and behind — at all times. However, pitching the idea to Detroit's major automakers didn't make sense to them, Urmson recalled. Self-driving cars, the authors argue, are "so transformative, in terms of safety, efficiency, the automobile’s environmental effects, that Detroit's appropriate response should have been a rapid embrace."

Undeterred, the team continued on, feeling "like we were working on something that would change the world, that would have a positive effect on many of society's most pressing problems, from pollution to the most basic challenge of just getting around our planet"” (p. 201)".

The remainder of the book chronicles:

potential calculations of profitability in autonomy
the difficulty in keeping the human driver's attention once lured into the calm of an autonomous vehicle - and accidents that occurred as a result of inattention
fleet transportation, historical analyses of job displacements (such as autonomy will create), the move toward commonplace understandings of self-driving technology with Tesla's self-driving software and other automakers' versions
the dilemma of disruption on established corporations, among others
The book ends with the acknowledgement that the mobility disruption will affect different people differently. The elderly will experience liberated mobility, while some current autoworkers many lose their jobs as a result of autonomous technologies.

"If we can pull it off," the authors conclude, "and we will, we're going to take 1.3 million fatalities a year and cut them by 90%. We're going to erase the challenges of parking in cities. All of that land will allow us to reshape downtowns. People who haven't been able to afford a car will be able to afford the sort of mobility only afforded to those with cars. And we're going to slow climate change" (p. 326).

(Daily Beast interview)

Autonomous cars are not a theoretical, maybe-if proposition that depends on a lot of different pegs falling into place. They're already driving themselves. You may have seen one beside you in traffic. (I recently saw one next to me at a red light, and it was weird.) There's already a full-blown trial in Chandler, Arizona.

If you bought a car in the last few years, there's a decent chance you won't buy another one. In a decade - maybe less - you may subscribe to a car service the way you subscribe today to Netflix or Blue Apron. When you need to go to Whole Foods, you send for a car on your iPhone or tell Alexa to send you one. Or you'll order Whole Foods online, and an autonomous car will bring the groceries to you.

The revelation that that comes through like high-beam headlights in Lawrence D. Burns's Autonomy: The Quest to Build the Driverless Car - and How It Will Reshape Our World is how much of the work is already done. General Motors introduced an autonomous concept car in 2002, and engineers started racing self-driving trucks and SUVs across the Mojave Desert in 2004. In the decade and half since, a long list of companies - Google, Uber, Tesla, Ford, GM, and many others - have spent tens of billions of dollars improving the technology to the point that it's ready for the world.

Burns, a former GM head of research and development and a current advisor to Google's Waymo autonomous car company, sat down with The Daily Beast.

When will I be able to order an autonomous car to take me to dinner? Two years from now? Five years from now?

It depends a lot on where you live. Waymo is testing its fleet right now in Chandler, Arizona. Within the next six month, a group of consumers in that market would be able to request an autonomous car to take them to dinner. This is a very big idea, but companies are starting small and picking specific places to prove out their technology and their value to the customer. I think you'll see it in a lot more markets over the next five years.

What's actually happening in Chandler, Arizona?

There are 400 individual riders who volunteered to participate in Waymo's program, and they have an app that allows them to request a ride anywhere within about a hundred-square-mile area, and an autonomous vehicle will come and take them to their destination.

Are the big things that need to happen in the next five years for widespread adoption of autonomous cars more on the business side - investment, manufacturing, distribution, etc. - than on the technological side?

We're much closer on the technological side and closer than most people think, but we're still not done. If the speech recognition is 99 percent there, that's not good enough for everything an autonomous car is going to handle in everyday driving. What remains to be done on the technology side is the very long tail, the 99.99 percent capability. Americans drive three trillion miles a year, and the machine learning still has more to encounter on the roads to be ready for widespread use. It's not just the software and the maps and the sensors and the vehicle actuation; it's all of that as an integrated system.

Do you see the deployment of self-driving cars being based more on geography than use case? I would have assumed that commercial applications like long-haul trucks would come first and personal use in different cities would come later.

Those are both happening. An important breakthrough in this entire journey was Level 4 autonomous driving, which was a standard set by the American Society of Automotive Engineers and subsequently the National Highway Traffic Safety Administration. A Level 4 system is capable of operating in a particular region during certain times of day under certain traffic conditions, and those boundaries expand going forward. At the same time, over-the-road trucking, last-mile goods delivery, gated communities, campuses, etc., are all areas where you're seeing progress in geographic expansion and use-case expansion.

You wrote in the book about figuring out three factors - shared-use vehicles, electric power and autonomous driving - that it would take for autonomous cars to succeed on a large scale. Is the shared-use part of that mostly about reducing consumer cost?

Right. It's important for driving down cost because you get much greater utilization with shared-use vehicles. Americans only use their vehicles about 5 percent of the time, which is poor use of capital. When you're not driving it, you're parking it. And 80 percent of the trips we make are 1- and 2-person trips, so we could tailor shared-use vehicles for those kinds of trips.

Will the automakers be hostile to that? Ford and GM won't be super happy about selling five cars to a fleet company instead of 10 to consumers.

Initially, it was hostile. Lately, it has been more embracing. I left General Motors in 2009 and had reached the conclusion as the head of R&D that the combination of electric vehicles, driverless vehicles, tailored-design vehicles and transportation services were going to really, really change how we get around. I led the research at Columbia University that concluded autonomous vehicles could disrupt $4 trillion a year of the U.S. economy.

I was doing this work in 2011 and 2012, and the auto industry were still saying in 2014, 'Hey, this is interesting, but it's probably 20 or 30 years away.' The progress by Waymo, Tesla, Uber, and other companies finally converged, and the auto industry realized that the business model of people paying $35,000 to buy a car, insure it, finance it, drive it, maintain it, pump gas, look for parking spaces is ripe for disruption. The automakers didn't get it initially, but they get it now.

What will the business plan for an automaker be? Will they supply autonomous cars to fleet-management companies, or will they be fleet-management companies?

I think you'll see both of those. General Motors is going to build its Chevrolet Bolt with a self-driving system and is positioning its subsidiary, Maven, as a car service. Ford has indicated that it's going to have autonomous vehicles by 2021 that would be tailored for particular use cases. I think you're gonna see a range of approaches.

What will the emblems on the backs of cars be 10 years from now? Volvo and VW, or Uber and Lyft, or Waymo and Tesla, or something else?

The driving service could become the thing that gets branded. Take BMW, which has branded itself for a long time as the ultimate driving machine. The vehicles of the future will be the ultimate riding machines. We'll prize how smoothly the vehicle rides, how safe they are, where they can go, what the service costs. The branding could be built around those factors.

Do you think owning a car and using a car service will coexist for a long while like print books and ebooks do now?

I like that question, and I think the answer is yes. Autonomous vehicles and human-driven vehicles will both be on the road. One of the most important decisions Google made with Waymo was deciding not to wait until every car was capable of being autonomous before putting autonomous vehicles on the road. An autonomous vehicle is safer for the people in the autonomous car, but it’s also safer for everyone else on the road.

The speed of that shift from driving to self-driving will have a lot to say about whether new buildings have parking garages and where people will live. Are those the kinds of impacts you foresee?

One example I'm seeing is in construction. If you're building a high-rise condominium in a city that has a requirement for a certain number of parking spaces that could become obsolete in the future, builders are starting to anticipate with ceiling heights, wiring, plumbing, etc., how they could cost-effectively convert that space to condominiums. If cars don't occupy as much real estate, I think you're gonna see increased density that will actually make the cities more walkable and make many cities more livable than they are today.

Do you see a big difference in the way dense cities like New York and Boston adapt to this world vs. driving cities like Los Angeles and Atlanta?

This future will not be one size fits all. There are a lot of different transportation solutions emerging that will be able to serve different cities in different ways. In cities that have good public transportation systems, the last mile will become very important. That could be a two-person pod with a top speed of 32 miles per hour as a way to get from the transit station to the destination. A more suburban area will need a different solution with higher-speed vehicles.

You note in the book that 1.3 million people are killed annually in automobile accidents but that only 37,000 of those are in the United States. How is it possible that only 3 percent of worldwide automobile deaths are in the United States?

I'm glad you picked up on that. I started traveling to China in the '90s when General Motors was starting operations there, and the fatality rate per mile in China was 20 times what it was in the United States. There were a lot of pedestrians and bicyclists on the road, and a lot of cities weren't using intersection-design solutions that took those people into account. It was a serious situation. Less developed countries have many more traffic fatalities.

Do you see evidence that other countries will be faster to adopt autonomous vehicles than the United States?

The United States is ahead right now. That said, China, India, and Singapore are doing some pretty impressive things. GM developed a two-person, autonomous, electric vehicle called the EN-V for the Shanghai World Expo in 2010. There are huge opportunities around the world for autonomous cars to leapfrog the current transportation systems like mobile phones leapfrogged wire-line phones in many countries.

Given the advances in battery life and reductions in production costs that you'd expect over the next decade, will we need thousands and thousands of charging stations across the country for autonomous vehicles?

The people who subscribe to autonomous-car services will expect the services to make sure the vehicles are charged, so people won't have to charge those vehicles at parking structures and gas stations. The services will do that at depots, which will give them some economies of scale.

You estimated that the cost of long-haul trucking would drop by half once autonomous vehicles are implemented. Will a truck going cross-country stop at designated interstate exits to recharge?

When you get the driver out of an over-the-road truck, a lot of things change besides saving 64 cents a mile in labor costs. You can double the use of the vehicle because you no longer have a driver who is spending half the day not driving. The cost of vehicle design and parts will start to come down when you get rid of the windshield, the seats, the doors, the air conditioning, etc. The vehicles likely won't crash as frequently, so insurance costs will also come down.

I'll just be glad if they stop changing lanes every time I get behind one.

[Laughs.] I drive between Ann Arbor and Chicago a lot on I-94, and it's unreal how often trucks change lanes and how that feeds road rage. I'm on the board of a company called Peloton Technology that works to optimize the distance between trucks to optimize safety and traffic flow, and organizing the traffic flow of over-the-road trucks is going to help considerably.

In theory, a truck that doesn't have to stop half the day won't need to drive as fast or change lanes as often.

It also doesn't need to be as heavy. One reason the loads are as big as they are is that you're trying to spread the cost of the driver over as many pounds of freight as you can. That becomes much less of a factor when you no longer have a driver.

Do you see companies that have an enormous stake in transportation and delivery - Amazon, FedEx, Kroger, Walmart - being early movers right now? Are they all doing the same things to get to a more automated mode of moving goods?

Those companies are doing a lot of the same things, but they're also looking for ways to differentiate themselves for an advantage. The companies also recognize that not all interstate highways are the same - some are flatter, straighter, have different weather and different levels of traffic - so you may see freight corridors develop first in the areas that are the most conducive to autonomous transportation.

You have a quote from composer John Cage at the beginning of the book: "I can't understand why people are frightened of new ideas. I'm frightened of the old ones." Is that too cavalier about the potential unintended consequences of autonomous vehicles?

Unanticipated consequences are just that: they're unanticipated. It's paralyzing to spend all of our time brainstorming unanticipated consequences instead of stepping forward and learning. The potential benefits of autonomy are extraordinary measured in lives saved, emissions reduced, climate change averted, land-use improvements, and improvement of access.

The only way we can manage unanticipated consequences is to start learning what those consequences will be. When we come up with a new drug that cures a disease, we're weighing the lives saved by the drug against every possible adverse reaction to the drug. When we have an opportunity to bring a huge benefit forward, we should start slow, learn fast, and then scale up as smartly as we can.

You think we should move faster to adopt widespread use of autonomous vehicles?

The biggest risk is not going forward as fast as possible. With 1.3 million people a year dying on the roadways and the potential there to eliminate 90 percent or more of that, if we get to full maturity of this one day sooner, we save 3,000 lives. That's a big deal.

You sound enthusiastic about where things are headed. Does that come from being a kid putting together model cars? Does that come more from seeing the public safety benefits?

I had a life-changing event in the early '90s when I lost my hearing and was completely deaf for a year. And then I received a cochlear implant, which is a technology not unlike what we're talking about with automated cars. It's digital, it involves speech recognition, it requires batteries. As the technology has improved, I can have a conversation with you that's fairly normal. If it wasn't for an Australian doctor named Graeme Clark in the '70s ignoring everyone who told him that you couldn't stimulate the auditory nerve with electricity, I probably wouldn't be talking to you. I can't help but be an optimistic technologist.

Plus, we're almost there with automated vehicles.

Right. The other part of my optimism comes from leading R&D for 12 years at GM and seeing what we can do with improvements of lithium ion batteries, communications systems, and everything else. It has been remarkable to see what engineers can accomplish through fast learning cycles. And my enthusiasm comes from the fact that the automobile industry has been around for 130 years and is still extraordinarily wasteful.

Only 2 percent of the energy in a gallon of gasoline moves the driver in the car. We're not utilizing the capital of the car 95 percent of the time. We have three parking spaces for every car. All of that waste has been embedded in the transportation system for a century, and so many companies profit from selling waste. Autonomy gives us an opportunity to get out from underneath all of that.

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