This is Dana Perkins and you're listening to Switched on the BNF podcast. Autonomous vehicles might be the cars of the future, but following a flurry of venture capital and private equity funding about a decade ago, investment in the technology is looking a little more tempered this last year, failing to reach four billion US dollars for the first time since twenty seventeen. While Apple has taken a step back, green shoots have come in the form of Tesla's Robotaxi announcement.
In such a cash intensive industry, what autonomous vehicle strategies and technologies are appealing to car manufacturers well? To tell us more about this, on today's show, I get to speak with bnaf's head of Intelligent Mobility, Andrew Grant. We talk about the adoption of autonomous vehicles across different regions,
such as robotaxis in China. We also review the different levels of automation that are available on the market and discuss Tesla's potentially controversial decision to continue with cameras as sensors while other parts of the market are embracing the more expensive light our technology. B ANDAF subscribers can find Andrew's recent research note at BNAF dot com or at BNF on the Bloomberg terminal. It's titled driving the next
phase of electric Mobility in Europe. If you want to receive an update when we publish a future episode of Switched On, make sure to subscribe on Apple Podcasts or Spotify or wherever you get your podcasts and give us a review to share us with others. But right now, let's jump right into our conversation with Andrew about the outlook for the automated vehicle sector. Andrew, thank you for joining on the show today.
Nice to be here, Thanks Stanna.
We are here to talk about autonomous or automated vehicles, depending upon how you want to refer to them, and some of the developments in that space. Now, before we get to the Jetson's Cars of the future and where everybody's head kind of immediately goes when we think of autonomous vehicles, let's talk about those kind of at the lower level of the computer intervention here. So let's go
through level zero through five. Can you give me a bit of a definition first of all, what an autonomous vehicle is and then go through those different numbers of autonomousness.
Great way, of putting it down and thanks. Yeah, So definitions are very important in this space. Consumers need to know who's in charge of the vehicle as it's operating on the road. So there's various levels of automated driving that are defined by SAE International. That is the institution that used to be known as the Society for Automotive Engineers, and they have what essentially are six levels of driving automation.
I'll simplify that a little bit just for our purposes because it's useful to just bundle these into different categories. So you have your level zero and level one, where there's either no assisted driving or just partially assisted driving that will help the human driver on the road.
So is this the old school cruise control that's been around since my mother was driving me around?
Yeah, exactly. Get up to a certain speed, lock it in and you should be should be fine. Then you get to your sort of more sophisticated driving, your advanced driver assistant systems that start to come in at what is known as level two and level three partial and conditional automated driving. So in these circumstances, the human driver is still the one that is in control of the vehicle. The computer and the self driving system are really an
extension of that human driver. They are meant to help out make the driving a lot safer, but ultimately the onus is on the human driver to be in control. Now, at level three conditional automation, that means at certain stages and in very specific conditions which hopefully the vehicle manufacturer makes very very clear to the human driver, the computer is able to take over and do the self driving or drive the vehicle itself.
So what's an example of this is the self parking or is this if you're about to get in an accident, it breaks for you.
Yeah, so that parking is part of this, or automating parking where you don't actually have to do anything and the vehicle is going to do the parking for itself. But also it's specific location, so say on a controlled
section of highway that's been mapped very thoroughly. Mercedes Benz has come out with a product where it is marketed as a level three self driving system and under those conditions, it's the computer that is under control of the vehicle, but it can still notify the human driver that it needs to come back in and take control of the vehicle.
Okay, so I've got an idea of here we are zero to three. Now as we get up to four and five, what starts happening Now.
You're talking about a different approach to the automation of the vehicle. What you have here is highly and fully self driving vehicles, and we just tend to bundle four and five together. That's really where it gets really sophisticated self driving technology. The computer is in control, it's doing the driving, and the human can do other things while in the vehicle.
And what are some examples of cars on the road right now that are at that level four or five.
Well, there's a few cases of this, so probably most prominently, which is the spin off from Alphabet Google their self driving car project. So weimo's operating in Phoenix, Arizona, in San Francisco and testing in a few other places throughout the US. These are level four highly autonomous vehicles that are capable of operating without any human in the vehicle. They have a bunch of sensors, very sophisticated computing under the hood of the car, and they do self driving
on their own. There's a few other companies that are kind of pushing towards this space cruise. GM owned company was operating at the sort of level before an incident last year. And then there's a variety of companies throughout China that are operating at this level. So companies like Ponyai by do Or also operating these sorts of level four highly autonomous robotaxis that are available for public use.
Okay, so we have a lot of different topics to get through today, and everyone hold on to that zero through five. Zero being low, five being high, and the different levels of autonomous vehicle that working to talk about today.
But if it helps to simplify it a little bit, we just like to think of it as you've got your partially andconditional automated, that's your aid ass and then you've got your highly and fully automated that's your robotaxi. So those kind of two simple buckets of self driving. They're very different implications. They have different use cases, different financial opportunities. So we kind of simplified into those those buckets.
That does simplify it quite a bit. So we've got it in these two categories. Let's talk about the money for a second though. So about a decade ago, there was a flurry of activity and the VC space, and some of the PE companies were as well investing in this, And what I want to know is where does it stand now in terms of investment and kind of have those original VC investments turned into bigger investments. Have they
gone through the startup value of death? That sounds like there are a lot of fairly established companies that are actually trialing a lot of this technology right now in different parts of the world. But is it as much in the investor's i as it was, say a decade ago.
Well, the simple answer is no. So a lot of money's flowed into this space. You're talking about seventy five billion in private equity and bention capital investment that we've tracked over the last ten years up to the start of twenty twenty four. And that really peaked in sort of twenty nineteen when a lot of investors were getting on the idea of a general self driving computer that could operate multiple applications. It could do a robotaxi and
transport people. It could ultimately be applied to trucking. This driver could go anywhere and do anything. And then what we sort of had for the years since then is as there's been slightly less money flowing into the space, companies have had to come up with more specific use cases for their technology. They were pitching for very specific
applications of their technology. So while them was less investment flowing into the space in general, it was more targeted and more directed towards companies that actually were developing a business model. They weren't just going to solve self driving in general, they were going to solve a specific pain point for consumers or businesses. So funding's dropped off. It was about four billion dollars that we tracked that went into the space last year. That's not small by any means,
but significantly down from what we've seen previously. However, there's been some big announcements this year. Tesla's gone all in on this space. This obviously doesn't count towards venture capital investment because Tesla's are one of the biggest companies in the world, but they're spending about ten billion dollars this year just building out the self driving compute systems to try solve their self driving algorithms. Well, recently there's been
some decent sized funding deals. So Applied Intuition raised two hundred and fifty million dollars through one of its funding rounds, and then quite recently Waive their British owned companies raised one billion dollars, which is a funding amount that at a Series C stage is something we haven't seen in this space in a little while. So nice to see those big billion dollar deals coming back.
I can certainly see how from the end user standpoint, whether it's in a taxi or in a car you're driving yourself, that if this technology is working effectively, it's safer and you're ultimately in a vehicle that will you know, make fewer human errors assuming all goes right. Some companies have been decreasing their activity, while others have really been dialing up how their focus is on autonomous driving. You'd
mentioned Tesla was one of them. Can you talk about some of the other automakers that are in this space who are adopting this technology and really what their strategy is and what the use cases and why they think it's going to give them a competitive edge.
Yeah, definitely. So what's really interesting, maybe if I tie this back to why we actually are talking about self driving vehicles in what the listeners are are, we'll well know is very a Decarbonization Focus podcast and all the work we do at B and F is very decarbonization focused. Self driving vehicle technology is key to many automakers strategies.
If you are investing in self driving vehicle development, that means you may not be investing in some of the other things that you need to do to become an automaker of the future. In Tessa's case, they have laid off a big chunk of this supercharger division and are devoting more of their resources towards self driving vehicle developments.
Other automakers have gone the other way, where they have kind of cooled it a bit on some of their self driving vehicle ambitions and are focusing more on, say, operating more connectivity services. Maybe they are focusing more on aid asas and developing technologies that they can actually sell
to consumers these days. Where this becomes really interesting is are you holding out for kind of a long term revenue and profit potential of some of your highly automated vehicle systems, or are you going to try make most of your money from aid asas and selling partially in
traditional automation to consumers today. So I would say the majority of traditional automakers are tending to focus on those level two level three self driving systems and selling the host to consumers because as some of the modeling that we've done shows, that is a big potential revenue driver.
How much do these systems cost and are they only found in luxury vehicles, because you know, if it sounds like it's the technology of the future, I'm going to guess that it's actually going to be a real premium and you're actually thinking about a vehicle.
I mean, it's a definite added cost. It can be ranging from a couple hundred dollars for your level two systems up to a few thousand dollars for your more sophisticated level two what we can sometimes refer to as level two plus and level three systems. So that's a cost that sometimes the automaker will want to incorporate into the purchase price of their vehicle and sell it to the consumer with that price baked in, and sometimes they'll
want to charge a separate amount for that. And we keep talking about Tessa, but there's a really good example of this with the autopilot and the full self driving software package which I'm using inverted commas. There for full self driving because it is not in fact a full self driving software package. It is a level two partial automation package, and they charge between eight and ten thousand dollars for that to purchase that package and use it
within their vehicle. They have recently just cut the price on that down to eight thousand dollars, but it's a significant chunk that's added on top of the vehicle that's kind of depending on which type of test that you're buying, that's three to twenty percent of the cost of the vehicle.
Given that this is a show that focuses on how decarbonization is changing the industries that we cover, to what extent do you find that autonomous driving is included in with a car that is an electric vehicle? Do you tend to find these together or really is autonomous driving across any number of cars and there's no strong correlation.
Or there's definitely a very strong correlation between vehicles that are electric and vehicles that are self driving. So, first off, at the aid as level, a lot of the new vehicles that are being designed and packaged together, those tend to be electric vehicles. And while you're designing a new vehicle, it's much easier to add new technologies to that vehicle than it is to take an existing vehicle and then kind of pile this new tech on top of it.
So inherently the newer vehicles out there, the electric vehicles also tend to have aid AAS and partially automated features as well. But then what we've observed with some of the robotaxis there and the testing data that's out there, a really high share of those vehicles are electric, to the degree of about ninety percent of the kilometers traveled
in autonomous mode in California. Amongst all the companies that are operating there, and there's a list of about forty companies that are permitted to operate in California, ninety percent of those cometss were done now with electric drive trains.
Why do you think that is?
I mean a few different pressures. So one, you are going to be bringing in well a taxi service into an urban area, So it kind of makes sense if you are bringing it vehicle into an urban space, you might have some regulators that are looking at you with a close eye. Probably helps a little bit to have an electric vehicle as part of that. There are just going to be a lot more electric vehicles in the future. It makes sense to build on a drive train that's
going to be more prevalent. And then there are some technical aspects to this as well. So if you have a big battery, you are running a big computer on these batteries as well, so you're going to have to have a big battery in any case.
You've brought up the technology a few times. And then also Tesla, which then brings me to the different competing technologies that are being used at the moment. So Tuessla uses these cameras around the vehicle. And then there's lighter, which can you actually first explain what lightar is compared to a camera based technology, and then can we discuss kind of which ones are being used where and with what types of companies.
So LIGHTER is light detection and ranging. Think of it just as a laser, So it's a different type of sensor that's used in these types of applications. Of all the robotaxis that are currently on the roads, they all use LIGHTER. It's a great sensor for practical purposes. It's got great range, it can operate in a lot of
different weather conditions. It creates a very reliable three D map of what's happening in and around the vehicle and can really complement some of the other sensors that you're using in this space, so it will complement what the cameras see as well. The disadvantage of it is that it is very expensive. So the initial versions of this were uputs of thirty five thousand dollars for a single sensor. That's come down signif evantly and the technology has changed.
It's gone from being one very pricey sensor that would kind of sit on top of the vehicle, it would spin, it would do a lot of different things. Now light or developers have kind of broken that up into a bunch of smaller versions that are positioned throughout the car or around the car, and incollective do the same thing
but for a fraction of the cost. Now, for some developers, and Tesla being one of them that I would mention, are in the minority of the autonomous vehicle space, the price hasn't come down quick enough, and they don't see it coming down quick enough. You're talking still even at the kind of the best end, it's about five hundred dollars for one of these sensors, you need a couple of them on a vehicle. Some developers use up to eight of those, so it's still an added cost on
the vehicle that pushes up the price. And on top of that, you still need the cameras to be doing a good job. So the approach of Tesla and one or two other developers in the space is to rely on the cameras to create this version of what's around the vehicle and what's ahead of the vehicle, and not rely on these sensors that can push up the price of the vehicle.
So, given that Tesla's continued with the less expensive but the technology that's traditionally been working for them, is there a risk is light er costs continue to decline and the adoption becomes more prevalent, that Tesla could get left behind in this technology or at some point need to adopt it themselves.
I mean, Elon Musk has been very clear that he has no intention of allowing the incorporation of lidar, in fact any other sensors long range radar for dy imaging radar within the Tesla self driving ecosystem. So it doesn't seem likely that Tesla would be doing that they are taking a gamble that they will solve self driving with their advanced computing that they're building out and spending all
that money on. There is the potential that while they are working on that algorithm and pushing it ahead, they do just get beaten out by companies that are willing to lean on some of these other sensors and maybe take the additional cost of pushing up the hardware price of their vehicles. But there's also the option of, at some state which I would never discount, that Tesla does a bit of a U turn and ultimately starts to
incorporate some of these sensors as the costic lines. There's a report that's just come out recently that Tesla purchased two million dollars worth of LDAR from Luminar Prominent Ladder supply last year. So this is something that they are testing with, but all statements coming out of the company are that they have no plans to put this into their vehicles. So waiting with beta breadth for August eighth, which is the announced dates of the Tesla Robotaxi being unveiled.
Great. So, now that I have a good feel for the technology, I want to pivot a little bit to the regional dynamics. You know, we do this event in San Francisco every year, which is the BNEF Summit actually that takes place there and it's very focused on transportation. A lot of the people at the summit, both our team and the different clients that we have at the event, we're definitely in a lot of these robotaxis. So I saw it as a very real thing. There Where is
the adoption? Am I right in thinking that the US is a big adopter of the autonomous driving technology? And outside of the US, also where else do we find it?
I mean two definite leaders in the space, the US, with some states in particular being well ahead of others, and in China. So different approaches to how these vehicles are being deployed, and most of that's coming from a regulatory front, but you are looking at places like kind of southern states across the US where there are robotaxis being deployed, not just robotaxis, also some self driving trucks
that are being tested to a fairly significant degree. And then California with San Francisco and the Bay Area being the tech hub that it is, it's a prominent area for robotaxi testing and deployment, and then across China. So a lot of the major cities in China, ranging from Beijing, Shanghai, Muhan, are significant autonomous vehicle test hubs, but working quite closely with the regulators to deploy some of these vehicles.
So talk to me a little bit about the testing. How does that work as a test hub? You have this geo fenced area that the vehicles then ultimately operate in and then they collapse to a certain number of miles or people inside or people not inside. How do you go about testing the technology?
For the most part, that comes down to the relationship with the regulators. This is a new space. There's a lot of back and forth between companies that are looking to deploy these types of technologies and the regulators. They end up having to go through what we call a bit of a policy gauntlet. You I'll use California for an example. You end up having to get a first a testing permit from the California Department of Motive Vehicles that allows you to drive around with a human driver
supervising in the vehicle. Then you can get a driverless testing permit where you are allowed to take the driver out the vehicle. Then you are ultimately allowed a deployment permit from the California Department of Motive Vehicles and that lets you put your vehicles into into operation. But then you also need the California Public Utilities Commission to give you permission to transport passengers, either at a testing phase or for for commercial reasons, so you need a bunch
of different permits. Then you might need to go to the federal level and get permission. If you are using a custom designed vehicle as your robotaxi, you need the federal government to sign off on being able to operate that vehicle on public roads. So once you've got this collection of permits, then you need to go to the local governments and work with them to make sure you're not disrupting things that they're trying to do. And they have ways to limit and control what robotaxes are deployed
and how they're deployed. So these companies are building up big policy teams and regulatory teams that are working with regulators to design the right type of regulation. But it's really kind of iterative and step wise, and you kind of can't really go from Hey, I've built this technology in a lab and then two weeks later, I've deployed it on streets and people are using those robotaxes. It's very iterative and it's very building up the process over time.
So let's stay on the robot taxis for a minute. One of the things when we think about decarbonization is the fact that autonomous vehicles could drive down the need for car ownership because you can have more vehicles available when you need them. And also these robotaxis, well the driver doesn't need to sleep. They maybe need to charge at their battery yet, but they don't need to sleep, so you have much longer use of the vehicle throughout
the day. What impact does the autonomous driving technology have on the number of miles traveled for some of these vehicles.
That's a great question and something that we put into our long term electric vehicle outlook. This can be a kind of a foundational element in the number of vehicles that you need on public roads in the long run. So since the vast majority of robotaxis in our view, will end up being shared vehicles, they will either be owned by a company or a central entity and shared amongst many users. That means that they will be traveling more than those privately owned passenger vehicles that will sit
in driveways or parking lots most of the day. Our estimate is that it's between three and five times the annual mileage of your private passenger vehicle. That means you need few of them to provide the same amount of mobility to consumers. So there are some benefits to that. If it's managed properly, you don't have to kind of have so many vehicles on the streets. You maybe don't need so much parking that you can use for for
other applications. There is a bit of a risk that some people are concerned about in that you would have a lot of what they call deadhead miles, which would be vehicles that are circulating looking for passengers, not parked, but just driving around and nobody's using them. So that's something that's worth paying attention to.
Which you do end up seeing with taxis and cities all over the world.
Yeah, exactly. And there's a lot of different ways to drive down those numbers, and you can kind of look at some of the databack solutions that some of the ride hailing companies are working with and they've had some success in driving down deadhead because ultimately nobody wants dead head. The companies that are operating these vehicles, the drivers that
are operating these vehicles don't want that as well. They are not earning while they are driving without anybody in the vehicle, so they're not trying to do that, and they want to limit those those types of miles.
I can't help but have a chuckle because my father is a grateful dead fan, and they are referred to as dead heads. So it is a sign of the times that we are using that term in a very different way. Right now, let's talk about some of the growth markets. So you had mentioned that adoption is quite high in the US, China coming is in a close second. Where are we also seeing kind of the frontier markets for this technology, and where do you think we'll see growth in the medium term.
I think anyway where there's a dense urban environments that meets a few criterias, so well marked streets, decent weather is a big help for some of these robotaxi applications. And then governments that are I wouldn't say necessarily willing to be flexible, but are thinking about regulations in this space in a thoughtful way. That's kind of the minimum
criteria for this technology to accelerate and be deployed. So there's a few places where that is true, but yet more kind of regulatory developments is needed.
Well. And then let's talk about a growth market for Tesla specifically, So they have set up a pretty large project in China. Can you comment on that a little bit, Yeah.
Sure, So, currently Tesla's FSD, their full self driving name brand product which I mentioned earlier, is not a full self driving system, is not available in China right now. It's something that they've recently received permission or at least passed too critical milestones to be able to introduce their
technology in the market. Now. China is the world's biggest auto market, big potential for them to introduce this type of technology there, particularly when you consider this is kind of eight thousand dollars or whatever they are able to charge for it on top of the purchase price of the vehicle. So good a little earner for them. And since they've got these types of permissions, they can possibly start introducing this technology. But they're not the only game
in town. A lot of the local companies, particularly this new crop of electric vehicle automakers that China has are offering at least at an SAE level Driving Automation classification level. It's a similar type of technology. And from what we've tracked, those technologies are being offered at a much lower price than what Tesla would be potentially introducing this vehicle, so potential for them there but decent amount of competition.
And then just going back to this convergence between the self driving technology and electric vehicles and the battery packs that are in the electric vehicles themselves, how much of the battery does this technology really draw upon and does it really dramatically reduce the number of miles traveled by some of these vehicles, and is that really a concern? And really are there any other drawbacks to this technology that maybe I'm not seeing?
Yeah, I mean in some cases, so you have a few different providers of self driving computers rending from video to mobile eye that are all providing different compositions of computing power that end up under the hood of the vehicle and do the self driving. Now, the power consumption of these can vary, but we ransom some numbers and in kind of a worst case scenario, nearly half of the battery or the capacity of the battery would be
drained by some of these self driving systems. That's a lot that is kind of a worst case scenario number, and I would mention that as these different computers get iterated, it's something that is declining rapidly, So we don't expect that type of number in many real world applications as we progress. But also, if you're operating in a robotaxic capacity,
this is something that you can design around. So if you are getting to say a three hundred mile range vehicle, and you might be only getting two hundred miles out of that, that's something that you can design your usage patterns around.
We've talked a bit about the companies that are really going all in on this technology and prioritizing it as a part of their strategy. But can you give me some notable examples of those who have really backed away from it.
Well, one of the most high profile that's kind of recently cooled on self driving and in fact vehicles in general, is Apple up until the end of twenty twenty three, or we have data that shows that they were testing this self driving vehicle technology in California right up until the end of last year, so this has been a pretty recent decision they and then they have decided to pull back on self drive VIA and that after years of trying different strategies of they're going to be a
fully self driving robotaxi service, they're going to be a partially automated vehicle that will kind of compete with your traditional automakers. Eventually they've decided that they are going to
pull back from that. And there's probably a few different reasons for that, one of them being the competition in the space, but also the complexity of this environment and balancing the need for an electric vehicle and a self driving vehicle and all the other technology that goes into these applications.
Well, and actually you've mentioned there were a lot of companies and a lot of activity about a decade ago. Presumably there are a few companies that are now left is emerging as the leaders in this space as the industry I mean, actually, has there been consolidation or has it essentially been that just some companies have really pulled out in the lead.
There's definitely been a lot of consolidation and a lot of companies that have pivoted to specific applications. So a company like Aurora, for instance, started off as a robotaxi developer, they now focus almost exclusively one large application, heavy duty trucks and doing long haul driving. And then there's companies that have been bought up and are now part of
much larger entities. Zoos, for instance, one of the more prominent companies and one of the more active robotaxi testers within the US and within California, is now a subsidiary of Amazon. So a lot of the tech companies are very interested in the space and have some interest or some venture. Microsoft placed quite recently a big investment in Wave,
so the tech companies are monitoring this closely. So it's interesting to see Apple pull out while a lot of the other tech companies are still actively involved and funding their adventures.
And you bring up an important part of miles traveled and really how goods get from place to place in supply chains, which are trucks and delivery vehicles. Beyond the robotaxis and the consumer vehicles that end up having all these safety features added, are the delivery trucks in our supply chain vehicles. A huge part of this market or is it kind of a little bit slower to react to it.
Trucking is a really interesting use case because if you really think about it, a lot of the applications seem like there might be some of the lower hanging fruit of the space. If you are driving from one point to another, you know a start points, you know an end points. If you are doing long haul trucking, particularly across the southern US where a lot of these companies
are located, you're dealing with pretty good road conditions. It's pretty decent and consistent weather the whole time, and for the most part, it seems like regulators are fairly open to some of these solutions that seems like the perfect combination. A lot of the trucking companies haven't been able to reach the stage where they are removing drivers fully from the vehicles for those fixed journeys, but there's a number
of promises that that will happen this year. So Aurora plus AI and Kodiacrobotics are all targeting to remove the driver from the vehicle during the course of this year and run some of those operations. So big things ahead for the self driving.
Truck space certainly something to watch. So we talked a little bit about how it changes the number of miles traveled for the vehicles themselves. But can you actually talk to me a little bit about how this changes the way they we interact with the vehicles and the way that people essentially drive, get around, receive their goods. What are some of the overarching themes and takeaways in particular given that we're BNF and we talk about decarbonization here, well.
I mean one of the main ways we think about this is just how it's changing how people would react in the vehicle and how the driving patterns that they would have if some of the burden of driving that vehicle is taken away or lightened. So there's some early studies out there, and this is kind of early data that show that people are more willing to drive longer distances if they have a reliable advanced driver's sistance system
in the vehicle that is helping them drive. Now, that's really interesting because it means that maybe people will be more willing to drive or prefer to drive longer distances versus taking a train or maybe a short hall flight or things like that. So it could really change the number of miles that are traveled on roads that obviously has a big impact on electric vehicle batteries. It has a big change on that number of vehicles that are
on the roads. So it's something that we're paying a lot of close attention to.
Yeah there, I mean, just the couple of examples you gave have huge implications. So fewer rail journeys may or may not end up increasing emissions overall, but actually fewer flights would certainly reduce emissions. So it really depends upon I guess what it's replacing and how it changes actually even where people live and how they commute to work
and how they go about their lives. So we'll watch this space and I look forward to seeing what analysis comes out of your team on how the future of vehicles and how we get around comes about.
Thanks for having me, Dana.
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