How I Built This with Guy Raz - When trucks drive themselves with Chris Urmson of Aurora

Episode Date: July 20, 2023

Chris Urmson is one of the founding fathers of the autonomous vehicle industry. He participated in three DARPA self-driving vehicle challenges before joining the team that launched Google’s self-driving car project, which later became Waymo. Eventually though, Chris saw an opportunity to scratch an entrepreneurial itch and bring his expertise to an industry that was ripe for it: trucking.This week on How I Built This Lab, Chris talks about launching and scaling Aurora, a company that is developing autonomous systems to safely drive semitrucks on America’s freeways. Plus, Chris and Guy discuss the impact that this technology could have on the U.S. economy, as well as the millions of truck drivers working in the industry today. This episode was produced by Chis Maccini and edited by John Isabella, with music by Ramtin Arablouei. Our audio engineer was Katherine Silva. You can follow HIBT on Twitter & Instagram, and email us at [e-mail] Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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It had tall windows, beautiful old details, and plenty of space for all of us. And being in that home on Airbnb, right in the middle of Vienna, walking distance from so much of the city, made it feel less like a visit and more like we were actually living there. Plus, taking a trip is the perfect time to host your space on Airbnb. Your place with all of its personal touches and its amazing location could make someone else's vacation even better. Your home might be worth more than you think. Find out how much at Airbnb.ca.com slash host. Hello and welcome to how I built this lab. I'm Guy Raz. So when you think about self-driving vehicles, you might imagine something like a robotaxie, you know, a car that can take you to work or school or home from a bar or a restaurant. In fact, if you live in San Francisco or Phoenix or a few other test markets, you can actually get a ride in a driverless car from a company like Waymo or Cruise.

In fact, I've actually ridden in one myself, and they're actually pretty amazing. But there is a whole other industry that will be affected by autonomous vehicles as well, and that's trucking. And it's a huge part of the economy. According to the American Trucking Association, there are about 3.5 million truck drivers in the U.S. But even with that many workers, there is still a huge shortage of truck drivers in this country. And that's a problem that Chris Ermson believes could be solved by autonomous vehicles. Chris's company, Aurora, is building an autonomous driving system that can operate everything from large semi-trucks to passenger cars. Chris has actually been working on autonomous vehicles for his entire professional career.

He was a founding member of Google's self-driving car program, which is now Waymo, and it all started. as an early fascination with science and robots. You know, as a kid, I was kind of mesmerized by the space program and the shuttle launches and, you know, enjoyed a lot of science fiction and thought robots were neat and built some out of Lego. And then as I was finishing up my computer engineering degree, I saw this poster of this robot crawling out of a volcano

and that had been developed by the folks at Carnegie Mellon. And I thought that was just really cool. cool. And my girlfriend, wife now, said you should apply. And so I did. And I got in and I got to go study robotics for five years or so. And, you know, it's exciting stuff. So you end up at Carnegie Mellon at a very interesting time because it was sort of like the beginning of the autonomous driving revolution. Most people probably were not aware of that at the time. We now know that it was. And I guess while you were there, you started to get into what would become autonomous vehicles. You started get interested in this technology. Tell me about when you first started to kind of see this

nascent industry emerging. Yeah, and it certainly wasn't then. I remember, so I had been there for a few years, and there'd been a lot of research in automated driving for decades before I got to Carnegie Mellon, and it was kind of in a bit of a lull. And I was down in Chile in the not a comma desert with a robot that we were using to study ways you could look for signs of life on other planets. So my PhD advisor, Red Whitaker, came down and told me about this DARPA Grand Challenge, which was this robot race from Los Angeles to Las Vegas across the desert. And he said, we're going to have to make a robot that drives 50 miles an hour across the desert. You know, I was there slow walking behind a robot, hoping it would work out in the middle of this

desert down there and thought, that just sounded awesome. And so, so, So kind of shifted the focus of the research I was doing, jumped into that with two feet. And originally the mission was about how do we keep our young men and women on the supply lines out of harm's way in conflict? And that seemed like a big deal. And then over the course of three of these Defense Department competitions,

the Darber Grand Challenges, you know, it moved from driving in the desert to driving in mock urban environments. And by the end of the third one, it was clear that this technology could have a huge impact on America's road. ways. Yeah, this first one in 2004, I mean, this was like, you know, sort of right in the middle of the Iraq War and DARPA was sponsoring all this, all these different kinds of

technologies, as you say, to kind of develop autonomous vehicles that could protect soldiers from, from, you know, being in harm's way. That first challenge, 2004, not a single vehicle, like finishing one vehicle managed to go seven miles. Maybe that was yours. That was ours. And it was still an amazing day, right? So we were stood in the grandstands at this place called slash x which is kind of a biker bar out in the middle of the desert and that was where we happened to launch from and i remember standing there and i was part of the team that launched our robot in the morning and you see this thing just drive off into the desert and we happen to have this giant fin on the top of it for some reason and you could kind of see it over the sagebrush and as it you know it left and it drove

you know 40 miles an hour off into the desert and it got like you said about seven and a half miles out of what was supposed to be 130 miles, I think. And the poor thing got stuck up on a berm, the wheels spinning. It was, you know, and the wheels were just touching the ground, so they were melting the tires, a big plume of smoke coming off of it. And so it was amazing, one regard, right, to see these things go off. And you had this kind of, like, sending your child off to school for the first day, where, you know, it's off in the desert by itself.

And then the heartbreak of the fact that you were hoping it would go 130 miles, and we went seven. There was a huge leap between what happened in 2004 and 2005. 2005, a bunch of cars finished. You guys came in second to the Stanford team. What happened in that one year to make that leap in technology possible? Yeah, well, I think that what was really exciting about the challenges was that it was an opportunity to focus a bunch of research that was happening broadly and kind of bring it together on one mission, if you will. And unlike most academic work where, you know, the idea is to kind of have the concept and you get the robot to do the thing once and you shoot the video and then it doesn't matter if it ever does it again or if it ever did it before, you've kind of made the point.

Here, it was truly a race. And so the thing had to be reliable enough that when you kicked it out the shoot first thing in the morning, that it worked the first time when it was off on its way. And so there was, you know, there was a lot of neat ideas we put into it. This was the first time where you saw the whole conglomeration of what is now a self-driving vehicle. We had LIDAR radar camera. We had machine learning. We had high-definition maps.

All this stuff that is now making vehicles kind of come together in a moment to solve this problem. And it was still a bit surprising that we made as much progress as we did in those years. But there's a lot of people kind of worked very hard and enjoyed the thrill of making the thing happen. Yeah, I mean, it's so interesting because so many people have gone on to found to start their own autonomous vehicle companies have been part of, we're part of these challenges. You, Sebastian Thrun, Kyle Boteu started Cruz, Dave Ferguson, founded Nuro, both of those founders were on our show in the past. What do you think it was about those challenges that just kind of captured the imagination of this cohort of people who you know, who you know?

You don't know them. Yeah. Yeah, no. And it is, it's one of the great successes, I think, of government funding, right? And it's kind of hit that sweet point between out there enough that it wasn't kind of a trivial commercial process, but close enough that there was a next step to be taken beyond it. And, you know, it was simple to explain, right? We were racing across the desert.

It was technologically achievable, apparently, but it didn't feel. like it on the front end. And I think there was an element of the competition part that was attractive, right? Like, you know, part of being an entrepreneur is you have to, you know, you have to want to win. You have to have the grit and determination to push through things. And so I think there's there's some element of kind of the human spirit part of it that, that enabled it to be as successful as a husband. Going back to that time, was it clear to you that this was, this was the future of travel, driving? I would love to say yes, but the honest answer is not in 2004, 2005. It was,

for me at the time, it started out as this is really cool. This is an amazing technology. I get to go drive Humvees in the desert and lasers and cameras and computing. It was just exciting and interesting and very cool. And then as I started to learn about the challenges our troops were facing out in the world and how complicated supply lines are, you know, and how fun vulnerable our troops are while they're operating those vehicles and how much, you know, we lost more people on the supply line than we did on the front line in Iraq. Yeah. And so that became, okay, I get it.

This matters. And then the 2007 challenge was a little different. So it was the urban challenge. And here, instead of driving down a trail in the desert, we were driving on a retired air base, so on the road. And we had to be on our side of the road. And, you know, got to collaborate with General Motors and Continental for the first time. and, you know, starting to talk to them

and kind of widening the aperture to start to think about, oh, geez, like this is actually broadly applicable and there's a chance here to, you know, take a real bite out of the 40-some-thousand Americans who die on the roads and make it more accessible. Like, it started to really gel

and then really became clear to me how important this was and how transformational this will be for society and for the economy and how important it is that we actually see this technology make it to market. All right. So before we, you know, sort of go down that rabbit hole too deeply, just give me a sense of why, of how you think self-driving vehicles will make our lives better. So when I look at self-driving vehicles, first we see the opportunity for safety.

40,000 Americans, 1.5 million people killed globally in traffic accidents. It's a pandemic. And it's something we can address. And this is the technology that will address that, well, continue to give people the freedom that they expect and want to be able to move through the world easily and freely. I do expect that we will give freedom back to people who have lost the ability or right to move around, whether it's because of illness or injury or age. There's some people who aren't or shouldn't be driving and in our society, if you can't drive to get somewhere, you become isolated. And that has devastating social and physical impacts on people. So So keeping generations engaged together, I think, is incredibly valuable.

And we should be able to level the accessibility of transportation, that cars are only becoming more expensive by providing ubiquitous, highly efficient, clean, safe transportation, will be able to level the social playing field for all of society. We're going to take a quick break, but when we come back, how Chris Irmson helps start Google's secret self-driving vehicle program, and why he eventually left that job to found his own self-driving vehicle company, Aurora. Stay with us. You're listening to How I Built This Lab. One more thing, before we get back to the show,

please make sure to click the follow button on your podcast app so you never miss a new episode of the show. It's usually just at the top of the app. And it's totally free. Welcome back to How I Built This Lab. I'm Guy Raz, and I'm talking with Chris Ermson, founder of Aurora. All right, so after these DARPA challenges, You were recruited to go work for Google by Sebastian Thrun, who was kind of like one of your rivals during these competitions.

He was the head of the Stanford team in these startup challenges. And I guess he recruited you to come work at Google on the secret project at the time, which was an autonomous vehicle project. Tell me about how did they describe it to you at the time? Yeah. So this was 2009 was when I started at Google. And so Sebastian and I had been competing in these challenges. But, you know, it was a friendly rivalry. We all kind of got that this, there was a race, but it was about moving this technology forward.

And we had talked about doing something together and thought about a couple of different ideas. And eventually, Larry Page had said to Sebastian, you know, why would you do this outside? We, you know, we want to do this at Google. let's put a team together. And so I was there to help found the team at Google. And it was a very secret project. Nobody knew that we were doing it, you know, because, you know, they wanted to be able to take a risk and try something out there and see how it went. And it kind of had this dread pirate Roberts feeling to it. When I signed up, they said, you know, we'll give you two years to go do this and then we'll probably fire you. But, you know, it should be fun in the interim. And so,

So my wife and I and our kids moved out from Pittsburgh to the Bay Area. And at the time, it was a very difficult decision because I just joined the faculty, Carnegie Mellon, and that had kind of been my aspiration up to that point. And they're like, well, you know, when are we going to have a chance to go visit with the crazy people in California and wear Birkenstocks and all that? And, you know, but it felt like a difficult decision. And in retrospect, it probably should have been the easiest decision in my life. Well, as somebody who's wearing Birkenstocks right now, I can say that was a

probably a good decision because they're great shoes. Exactly. But seriously, so you get to Google and in the challenge is what? I mean, you were given a challenge to create a fully autonomous vehicle like that can go on the roads. Like what did they tell you they wanted to accomplish? Yeah. So one of the brilliant things they did was take the DNA of the DARPA challenges and kind of bring it internally. And so we were given two goals, really, to drive 100,000 miles and pull.

public roads and then to drive a thousand miles of very specific roads that Larry Page and Sergey Brin had kind of picked out as ways to kind of make sure that we had both the breadth and depth of performance and from that we'd be able to figure out like is this 50 years away or is it five to 10 years away and thus whether it's worth kind of a company spending resources on it and so you know the 100,000 miles was pretty straightforward we mapped a part of the freeway in the Bay Area here. We had a bunch of cars that just kind of went up and down it. We learned from that and refined it. And then the other was driving a thousand miles of really interesting roads where we'd have to kind of push the capabilities so we could really understand, like, is this viable?

And so it was things like driving around Tiburon. Tiburon is sort of a peninsula in the Bay. It's just north of San Francisco for people who aren't familiar with it. It's, yeah, I mean, it's a tiny, tiny road that just kind of leads to the town and goes around the peninsula and that's it. It's actually, for part of it, is one lane for both directions, which is fun. And then there's another road called Page Mill here, which is this windy road that winds out of Palo Alto

up to the top of the mountains here. And it's a very popular road for cyclists. I write there pretty regularly. So, you know, a nice breadth of different types of roads and driving. And so we ultimately completed both the 100,000 miles and this thousand miles of interest in roads within about 18 months of starting. I mean, at the time, did you feel like

it's just a matter of time, just a matter of maybe a few years before this is normal. This is deployed everywhere. We're going to see this all over the place. Or did you still think it was a long road ahead? No, I think, you know, it was clear that both were true,

that this was going to happen and that there was a lot of work to be done. And I think in 2012, I said something about working to make sure that we had self-driving vehicles before my son had to get his driver's license. And so we missed that by a little bit. And I didn't miss it by much because my younger,

my older son still hasn't got his license. So my younger son just got his license, you know, two weeks ago. So, you know, I feel like in the grand scheme of things, that doesn't feel like a terrible estimate in retrospect. Yeah. But, you know, what's exciting is that today, you know, in Phoenix, in San Francisco, in L.A., you're actually able to get a ride in a self-driving vehicle.

Yeah, I mean, I've been in one of those vehicles in San Francisco, and you see them driving around. And it's still quite amazing to see a vehicle with not a single human inside just driving the streets. And of course, they're not perfect yet, but it is pretty amazing to see it. It is. And it's one of these things that will have a profoundly positive impact on society. All right. So you eventually left Google to start your own company. And tell me a little bit about, first of all, what makes a world different from your competitors?

Because there are obviously many of their competitors you know. You've known for a long time. Yeah. Who are working on similar types of technology. Yeah, I think when we founded the company, part of the thesis was if we brought the right people together with the right experience and the business model and the kind of the collaborative spirit that we could actually have a bigger impact than trying to build something in isolation and, you know, be a disruptor, quote, unquote. And so for us, we're focused initially on trucking.

We see that as a gigantic, exciting market where long-haul truck drivers, they're 10 times more likely to die at work than an average American. And they spend all this time away from home and they don't get to see their kids or their wives or husbands and so helping goods move more efficiently helping that become lower cost over time we can have a huge impact on while addressing this critical shortage drivers we have and helping the us economy and that's good for all of us and then we've made some really important technological bets so one of the core technologies we have at the company is we call it first light which is the special lidar technology so light is using light like radar and it allows us to to see farther than other

people can and see how fast things are moving instantly. And so for driving trucks, you have to see a long way down the road. And first light enables us to do that. And then there's a variety of other exciting ways we've folded machine learning and AI with classical algorithms to make our system really robust and human-like in the way it drives. Can you sort of, I mean, sort of explain the difference between developing a driver that can handle a semi, a large truck and a driver that is driving a taxi? Is it a different type of technology that you have to develop for a, you know, a long-haul truck? So if you think about it up front,

there's a lot of commonality. And in fact, our technology can drive light vehicles and big trucks. But there's a few big differences. So one is if you're driving at relatively low speeds in a city, then you don't have to look as far ahead because it doesn't take you as long to stop and everything's moving a bit slower. Yeah. And then if something breaks, you can basically just kind of stop where you are, kind of move a little bit to the right and everybody's kind of moving slowly so it's not that big a deal. Whereas if you're driving a truck down the freeway at 65 miles an hour, you have to be looking

out 400, 400 plus meters to see what's happening because there's so much momentum and inertia with that thing. And you can't just kind of stop in a freeway lane. You have to be pulling to the edge of the road whenever possible and getting out of the way. And so the way we've architected our system is that it can span from the high-speed stuff and the trucks down to the light vehicles as well.

And if you think about a, you know, if you want to become a truck driver, you have to be able to drive a car first, right? So there's a lot of common skills that are used, whether it's understanding traffic and thinking about how to maneuver a vehicle and kind of that level of intuition. But there's an extra chunk of stuff you have to do to move from driving a car to a truck. And essentially, and correct me if I'm wrong, but I mean, you are basically building an autonomous driver.

That is, you're not building vehicles. It's not vehicle specific. You are building the technology that will essentially could replace a human driver. That's exactly right. So we look at ourselves and we think, okay, the thing we can do best in world is build that driving capability. And there's companies out there that have been at it for 100 years that build vehicles and they've got a whole lot of battle scars learning how to do that well. Let's work with them rather than against them. So I mean, give me a sense of where your technology is now.

Because so we have these different levels, right, of autonomous driving. There's like level, you know, zero, one, two. Let's first talk about like level two, which I think is where, you know, cars that have of some kind of automation like Tesla's, right, which are called, the Tesla calls itself a full self-driving, you know, system or whatever it calls itself. But it's actually not autonomous, right? It's not designed to drive without a human intervention. That's right. And there's kind of a really simple way to think about it. So level zero is your classic Corvette. And it's basically, it's a steering wheel and breaking gas pedal and a clutch and, you know, very manual. And then level one and two are systems that are designed to help

a person. So there's a person who's responsible for driving. And whether it's the Ford collision warning system or Ford collision assists, so if you're about to hit something, it hits the brakes a little bit before you do, or lane keep assist. You know, a lot of modern cars have these kind of features. And so if you have one of them at a time, then it's level one. If you have kind of in lane and along lane control, that's level two. And then we'll not talk about level three because that's kind of a confusing place. But when you switch to level four and five,

instead of the system assisting a human driver, the system is actually driving the vehicle and the human is really along as a passenger. And so for us, the systems we've been building from day one are aspire to be, are intended to be those level four systems. So it does all of the driving. So our trucks will leave, our terminal, drive the frontage road, get onto the freeway, drive down the freeway, get onto

the frontage road, drive through the commercial neighborhood, and pull to their terminal. And they do that end to end. And then we today operate with people on board who are checking the system. They're there in case something isn't behaving the way it's supposed to, and, you know, to kind of monitor and provide feedback to our engineering teams who are continuing to make that system better. You in earlier in 2023 you announced that you had achieved essentially you achieved level four autonomy, that your technology is essentially ready to go. We're a little, little nuance from that. So what we said was we achieved feature complete, which means that we do all the things at this point. So all of the skills that we think the driver needs to have to be able to get from a terminal

to a terminal are in place. And so for the next few months, we're going to be focusing on confirming that all the things work the way that we expect them to and need to to be confident in the safety of it and refining in the places where, you know, through that testing, we identify shortcomings to get to the point where we aspire at the end of this year

to be a roar driver ready, which at that point means, yes, it's ready to go. We've kind of met the first point where we would be willing to put the, truck out on the road with nobody in it. And, I mean, is the intention, and I guess maybe it's not really up to you to decide that, but once you make, you know, sort of have perfected, let's say, the technology, it's up to the partners, whether it's, you know, Hyundai or Kia or whoever is using it to decide

whether that vehicle will transport goods or people, right? Well, yes. And the way we think about it. it is if you're FedEx, who's one of our partners today, what'll happen is you'll call up Packar and you'll say, I'd like to buy a Peterbilt 579, which is a long-haul truck. Packar is the company that makes the vehicle. Yeah, they make the truck. And we want to get that truck and we want to buy it with the Aurora driver installed on it. And so then that'll come into the FedEx fleet.

And then when the Aurora driver drives that truck, FedEx will pay us for driving it. for them is kind of the way to think about the business. Right. We're going to take another quick break, but just ahead, Chris talks about the potential challenges of operating an autonomous trucking fleet, and what am I mean for the millions of people who are working as truck drivers today? Stay with us. You're listening to How I Built This Lab.

Welcome back to How I Built This Lab. I'm Guy Raz, and my guest is Chris Irmson, the founder of the autonomous trucking company, Aurora. Chris, as somebody who's worked on this, your entire professional life now, you encounter, I'm sure, skepticism now and again, maybe not in the day-to-day work environment, but outside of it you do. And it's understandable, right, because people are thinking, okay, here's a semi-truck, right? And it's being driven by a machine. And I can intellectually, I can understand and accept even why a machine will be a better driver than a human.

I think they will be. But at the same time, you know, I still think about, well, what about, you know, just weather conditions or road? Like the ways that a human driver, an experienced truck driver, knows how to operate in extreme weather, you know, a horrible storm, snow, just things that seem nuance. I mean, the technology can solve for all of those variables? Yes, is my expectation. And again, I don't want to oversell where we are today. So today there's limitations on, you know, the weather conditions that we're willing to let the trucks operate in. but I think about fog, for example.

So fog is something that'll, you know, a lot of accidents happen in fog. Yeah. And they happen because people operate in what I call faith-based driving mode. So they look out in front of them. It's dense fog. They don't see anyone. They're like, oh, I'll just keep driving at 65 miles an hour. Yeah.

And then, of course, somebody had to slow down in front of them and you get an accident. And then the person behind them, you know, was doing the same faith-based driving kind of mode and crash in the back of them. and you end up with 120 cars on the interstate, whereas the way the automated driving system will work, the Aurora driver will understand, I can't see as far as I normally can. That means I should slow down. That means that I will be able to respond

in situations where, you know, somebody's had to slow down in front of me because I've got enough distance to stop. And so you're taking the impatience, taking the ego out of driving, you know, there's a place for that, right? if you're on a racetrack and you're you're enjoying the sport of driving, great. Go do that, enjoy it, right?

That's a human pursuit. But the mundane part of getting from A to B and doing that safely, reliably, efficiently, right, it's a place where we can have a huge positive impact. Yeah, I mean, and I always come back to this idea, and I know you've been asked this a million times, and, you know, and this is a conversation that comes up. But again, I'm not convinced it's the right question, but it still comes back to me because I think it's worth exploring, which is, yes, there is a shortage of human long-haul drivers. We know that. There's a, you see these drivers at truck stops and most of them are older, tend to be older men. You don't see a whole lot of young men doing these jobs because they're hard and you have to be away from home for days or weeks at a time. But at the same time, I still wonder what happens when we have a world. of totally driverless long-haul trucks. I mean, on the one hand, you know, statistically, we probably will be better off, fewer accidents, more efficient cars. But at the same time, it does, I mean, you are talking about humans who do these jobs. What would those people do instead? Yeah, and I think it's, it is really important to acknowledge. I say this regularly. This is a really

important job. It's a really difficult, dangerous job, and we should all be incredibly thankful that there are people willing to do it. At the same time, there's an opportunity to make society better and for these folks to ultimately move to other jobs. Now, my expectation is that if you're driving a truck today and you would like to retire as a truck driver, you're going to be able to. The shortage is that dire and the opportunity to kind of grow the freight market is real. So I expect that, again, you'll be able to retire trucking as a truck driver and you'll be able to get a better job. Instead of having to drive a long haul, there'll be more demand for, you know, local hall.

And, you know, I see a real opportunity there. We're also working to put training in place for the jobs the future around maintenance of these vehicles. We, you know, we have folks who've transitioned from our operations driving team to working in our command center, which are helping support the remote operation of these vehicles. There's going to be all kinds of interesting roles around the terminal. So these will be much like the rest of the arc of technological advancement, where there's disruption that displaces certain jobs. We almost universally look back on it and say that both increased the quality of life

for society in general and actually increased employment. You always have to think about the human side of this, and you have to have empathy for those folks that ultimately will have to make a change. But I think in this case, the ramp is going to be such that they will have the option of whether they want to make that change or whether they want to continue driving. So I've seen that the expectation is that the commercial service will launch by the end of 2024, which is, you know, it seems doable but also ambitious, right? I mean, just because of the, there's still probably some regulatory hurdles and also just safety. I mean, what you're working on, like there's just zero room for error. And this is where we're really proud of the work we're doing.

So we've shared publicly how we think about safety. And we've shared this thing we call a safety case, which is how we're going to convince ourselves that this vehicle is safe to operate on the roads. And it spans everything from when it's working. working properly, does it drive in a way that's safe? If something breaks, does it know about it and kind of handle that in a way that's appropriate? Have we thought about how it protects itself if somebody tries to attack it? Do we learn from things that have happened so that we're constantly improving? And do we have a company where we have the right procedures and the right culture and we're trustworthy

to kind of deliver something like this? And one of the things that's really exciting is that we can use simulation tools to test, the driver against more events than a person will see in a lifetime. So today, one of the things we do is we look at all the ways vehicles can get into crashes and we build simulations of those. And we actually expose the Aurora driver to them. And it's tens of thousands of these things. And we see how it responds. And that level of evaluation is something we just wouldn't ever be able to put a human driver through. So by the end of 2024, when this is now, commercially available do you expect a company like FedEx to be hauling goods in a

FedEx branded truck that is autonomously driven so today we haul goods for a number of our partners and so there's an Aurora tractor with a FedEx trailer or a Hirschbach trailer or a Warner or Schneider trailer and you know we do this with a person in the cab yeah monitoring driver but we're we're being paid to haul these goods today. And so, yes, our expectation is by the end of next year, there will be no human. Yeah. And the way we're going to launch this is initially it'll be on one lane, which is what you call kind of a trucking route. And that'll be between Dallas and Houston. And then we'll expand likely Fort Worth to El Paso. And then we'll kind of grow the network

out from there. Right. And so the difference between now and, let's say, a year or two from now is there won't be a human in the truck. That's exactly right. Yes. Wow. And so, I mean, when you kind of look out in, you know, in the future, like, I mean, you've been in this, you've been involved in this now for 20 years. Embarrassingly long, yes. 20 years, right? I mean, that first competition was 2004 and you were working on it in the years before. Yeah. 20 years ago, if you looked out 20 years ahead, you might have imagined things being maybe a bit different.

I don't know. It's hard to know. Maybe there were people involved in that DARPA challenge. I thought, oh, in 20 years from now, no one's going to be driving. And I think we've made some, I mean, people involved in this industry have made incredible innovations. But in 10 years from now, I mean, do you think that it's possible that 50% of the trucking fleet in the U.S. will be autonomous? I think that's probably high for 10 years for now, but it's going to be tens of percent is my expectation in a decade. Wow.

Yeah. And eventually, I mean, before the end of your life and mine, probably every long-haul vehicle will more or less be driven autonomously? I don't know if it's going to be every. We'll see. I may have a lack of imagination. But I think of, so if you think about the different kind of trailers you can haul, so today we haul what are known as drive-vans. So these, if you've seen kind of a box truck on the freeway, that's what this is. And then we also have recently started hauling refrigerated trailers.

So this is a box truck with a chiller on it so that you can ship lettuce or produce without it going bad in the back of the truck. We've also, we intend to haul intermodal trailers, which is basically you think of a box that can lift off of the chassis that has the wheels underneath it. And so those are all pretty straightforward. And then you get into some more complicated things. So liquid tanks, you've seen kind of the cylindrical trailers that are on the freeway, and those have fluid in them. And so if they're full, then they're kind of like a heavy box truck. But as you start to take liquid out of them, then they can slosh around. And so that one I figure we'll probably be able to handle, but that'll be a little further down the road.

The really most complicated and difficult ones are flatbed trailers. So these are ones where you have a piece of equipment. Maybe it's a tractor on the back of the trailer. And it's tied down with ratchet straps. And for those, the driver has to go out and do a bunch of inspection. and the weight's going to be kind of weird on it. So figuring out how you can, you know, how you make sure that the safety of that cargo on the back of the tractor is secured, you know, is another leap, I think. Chris, let me just sort of ask you to put on your entrepreneurs hat for a moment because there has to be a significant level of stress knowing that you're essentially overseeing a company, a business that with amazing technology, and I'm absolutely sure it's going to work.

But one mistake, one accident shuts it down for a while. I mean, if one of these trucks, even if there's a fender bender, it could be, you know, regulators and politicians calling for a suspension of the service. I mean, you're sort of at the mercy of fate in a way. I think that's right. But there's a lot we can do to help influence that. And we're seeing that it's not quite as dire as you're laying it out to be. So I remember back when I was at Google, you know, the first time we had a crash, it made national news. The second time we had a crash, it made national news.

The third time it made local news. And, you know, the fourth time people stopped reporting on it. Right. And, you know, it's not quite that sharper curve, but it's pretty close. And so I think that there's a level of transparency we can provide. there's a level of care that we have put into the work that can help insulate from some of that. For example, we were driving on a freeway in Texas, and another person was driving a car, they dozed off and sideswiped our truck.

Now, fortunately, everybody walked away. It was minor damage to the car, minor damage to the truck. We ran our protocol for what happens if an event. like this occurs and we informed the agencies both state and federal about what happened. We in fact shared a video on our blog about what happened and we think that level of transparency engagement will help. Unlike a lot of Silicon Valley companies, we have spent a lot of time engaging with the federal regulators and the state regulators, the DOTs and NHTSA and FMCSA, these are regulatory agencies at the federal government and helping them understand both the promise

and risk of the technology, helping them understand what we're doing, why we're doing it, how we're doing it, and bringing them along on the journey because they have an important, difficult job, and the last thing they need is to be caught flat-footed as something's happening. And we think that kind of transparency where people can understand what's going on, builds trust, and helps reduce the knee-jerk reaction that could otherwise occur. Chris Hermson, thanks so much. Oh, my pleasure. Thanks so much, Guy. That's Chris Irmson, founder and CEO of Aurora.

Hey, thanks so much for listening to How I Built This Lab. Please make sure to follow the show wherever you listen on any podcast app. Usually there's just a follow button right at the top so you don't miss any new episodes. And it is entirely free. If you want to contact our team, our email address is hibt and id.wondery.com. This episode was produced by Chris Messini with editing by John Isabella. video engineer was Catherine Silva. Our music was composed by Rumtine Arablewee. Our production team at How I Built This includes Alex Chung, Carla Estevez, Casey Herman, J.C. Howard, Liz Metzger, Sam Paulson, Carrie Thompson, and Elaine Coates. Neva Grant is our supervising editor. Beth Donovan is our executive producer. I'm Guy Raz, and you've been listening to How I Built This.