Cracking the code on autonomous trucking

Latitude Media covering the new. The energy transition. I'm Shayo Kahn. I lead the early stage venture strategy and energy impact partners. Welcome to Catalyst. So Waymo's first public ride service was in December 2018, years before the meteoric rides of LLMs that we've seen since then. And it's interesting to think about what's happened with autonomous vehicles, which were capable of driving on public roads, at least in some limited capacity, even back then.

Not all that limited, I should say, but limited nonetheless before the current wave of AI. Anyway, I was listening to an interview recently with the co CEO of Waymo, who described how they've been able to integrate the newer AI capabilities into their system. And how that's allowed them to basically supercharge their growth and to deal with a wider variety of edge conditions than they would have otherwise.

Obviously Waymo now is ubiquitous where I live in the Bay Area and increasingly is becoming so in many other cities. So the path to autonomy for light duty vehicles seems very clear. Less so at this point for trucking, though the market is huge. Trucks hauled over 11.2 billion tons in the last year in the US alone.

There have been a bunch of attempts at autonomy for trucking, and in some ways, it intuitively seems like it should be an easier challenge, but in reality, turns out maybe to be a harder challenge. We'll get back to that. Anyway, we just don't have this equivalent of Waymo in trucking yet. So what would it look like for someone to start fresh now?

fully immersed from day one in the new wave of AI, particularly in this context, having benefited from the advent of things like vision language action models, which is sort of an offshoot of LLMs aimed more at the physical world. By the way, I find autonomy interesting in its own regard. Uh given that autonomy really goes hand in hand with electrification.

We've seen that already in the light duty vehicle world. I think we're starting to see it now in heavy duty. In any event, Ayal Cohen is the founder and CEO of Humble Robotics, a company that we at EIP just announced we invested in a couple weeks ago. Ayal is a veteran of the autonomous trucking world. He worked at Apple, Uber, Spark AI, and Wabi before starting Humble. And his view is that starting with a clean sheet, both from a vehicle perspective and from a tech stack perspective.

Will allow Humboldt to dramatically accelerate adoption of trucking autonomy. So I talked to him about the broader world of autonomous trucking, where we are today and where we're headed, and what he's building at Humble. That's coming up after the break. When utilities need flexible capacity they can count on, they turn to energy hubs.

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If you want a PR partner that's thoughtful, shoots straight, and gets results, you'll like Fishtank PR. To learn more about Fishtank's approach, visit fishtankpr.com. That's f I-s-ch-h fishtankpr.com. Thanks for having me. I have a bunch of questions for you. Let me start with this one. Um

You know, Waymo has done 200 million miles now on public roads and is driving me all over the complicated and messy streets of San Francisco. So, you know, passenger vehicle autonomy is is clearly here and now across a bunch of cities. And yet we're not there on trucking autonomy. Why is that?

Well, that's a great that's a great first question. Um, you know, so I think we need to go back a little bit to kind of when autonomous trucking started uh and and the and the history there and it'll help explain a little bit of that. Um So, you know, there's been like unmanned military defense experiments for a long time, but from a from a uh an industry that's not in defense, um autonomous trucking really started in twenty sixteen. There was two companies.

Star Steer Robotics and and Otto. And I I was part of auto. I joined I joined pretty early. And I joined Otto at the time. I think there's some fallacies I think maybe that we had at the time or misunderstandings about the space of the time. Um, that'll help explain the the answer to your question. But when I joined, I I had been working on passenger car autonomy with with other efforts. I was in Apple for a bit. And the the challenge that I saw was

cities felt very hard. Like uh at the time, given where the tech was Uh we were just like, How are we gonna solve San Francisco and everything that happens in San Francisco? Um, and you know, the way the tech worked at the time and still for a lot of companies works this way, is we were doing this very complicated HD mapping procedure where like basically vehicles would drive and try to capture the world in 3D. Uh and

you know, trying to maintain this sort of updated high definition map in three D to locate the vehicle across to. It all felt very hard at the time. And uh when I learned about auto doing trucking, I was like, hey, this feels This feels like a more straightforward problem, has great commercial application. Uh why don't we go tackle that? I didn't know too much about trucking electric trucks and most most people are like in awe of like big vehicles, right? But

But uh the highways felt easier. And they felt easier because, you know, when you drive on a highway, mostly what you do is go straight. Um, and what it turns out is that actually the passenger cars have a lot of structural advantages in in developing an autonomous system that were very difficult for trucks on highway.

And so even in twenty sixteen when we were doing we at auto we did this um we did this uh beer run a hundred miles long uh with nobody in the front seat. It was you know, and everybody felt like, okay, a Thomas trucking is right around the corner. You know, what we're what we found over time is

Uh, the highways were way more difficult than we expected. They're they're challenging. I mean, by the way, my my premise here is that everything will get automated and passenger cars just happen to be first, but everything will get automated. It's it's just the sort of the march of the technology, the progress.

But the highways we thought would be easy, they turned out to be hard because of edge cases. Um, you know, uh you're driving at a higher speed, you're talking about a vehicle that could weigh eighty thousand pounds uh in some cases. um if it's at full gross weight and your stopping distance is long. Uh trucks just have challenges on highway that make them more difficult. Would it be would it be accurate to put it as like

On a highway, you probably have fewer edge cases than you have on like a San Francisco street, but it's harder to manage. It's harder to deal with those edge cases because you're going at high speed in an eighty thousand pound truck, et cetera. Yeah.

Yeah, I think uh probably like different kinds of edge cases, the way I would put it. Um the you see them rare you see them less often, which is one one key issue. Like a lot of the times we're driving on the highways, nothing happens. And I usually actually joke that like you could just take a

a truck with no perception system and put it on the highway. And as long as it stayed in the lane line and stayed at 55 miles an hour, it could probably complete 200 miles with no issue. It's just that occasionally things happen on the highway that are very difficult to manage. And you don't see those

events very often to be able to handle them and and and learn from them. So that that's one challenge. Another challenge is that You know, the the truck, the the passenger cars, like a Waymo, you know, when they are confused about what to do, uh, when the robot doesn't know what to do next, it can stop.

It could stop and obsess. And uh it's annoying and I'm sure you've seen videos of Waymo stuck, right? But it's mostly annoying, not a hazard. Uh so when in s in San Francisco, when a passenger car stops, you know, people go around and they honk, they call, they call uh they call annoy their their local politicians, whatever, but mostly it's n it's a safe s situation.

you don't have that advantage on a highway. So stop so stopping a truck on the highway is actually extremely dangerous. Um and could easily cause an accident, uh especially if there's like a a bend or a hill where you don't see. Uh, you know, it's trucking, the margin for error is less. So so all these things just sort of started to pile up in trucking. And I think it just took longer to solve. It will get solved. Um, but uh

I think we in twenty sixteen, when I started with the the auto, auto and star ski, we thought they were easier. It was easy it was gonna be an easier road. And just turned out that though we had some misconceptions about the space. And so where are we today in terms of autonomous trucking? I mean, you said auto and starsky were the the first two. There have been a a bunch of other, I guess, what I would call serious attempts. Since then, like how far have we gotten?

Yeah, many serious attempts, I would say, and and w by serious I mean real technology development, real capital, real um, real real efforts. Uh they've all kind of followed a similar blueprint, I would say. They take existing tractors that are that that have been manufactured by OEM, sometimes in partnership with an OEM like Volvo, uh, sometimes um just sort of buying from a lot and and and doing a quick retrofit.

Um and uh, you know, the attempts so far, you know, there have been a few driverless runs where and by driverless I mean nobody in the front seat. There's a lot of like sort of debate about what driverless even is. Right. Uh for example, I think Aurora, which is one of the largest players in this space, you know, they do what they call driverless runs, but they they sometimes have a safety observer. This is from their public.

Public writings. Um, somebody sort of sort of watching the system, but they they call it driverless as in maybe they don't touch the wheel or engage in any way. Um, so there have been driverless runs, even going back to that 2016 uh auto. Um, there was a company, there's a company in Bot Auto that just I think yesterday did a commercial, what they call the first commercial driverless run. Um, I saw that on LinkedIn.

Um, but I would say there's not a regular driverless service for trucking on highway that exists today. Um, and that's uh ten years after we've really put serious effort into the space. And and five years plus after uh passenger vehicles really hit the like inflection point where those rides are getting taken, you know, all over the place in multiple cities now and even on highways now, as of more recently, of course. Um

So yeah, so it's interesting. And I think like when you take a step back, surprising because I intuitively I would have thought the same thing, I guess, that you intuitively thought, which is that like all things equal, you would think trucking is easier. It's just like less fewer things going on on a highway than there are certainly in the streets of a a dense city like San Francisco. But yeah, it turns out that those things are harder to harder to handle.

One thing I'm curious about though is that this first wave of autonomous vehicles, both trucking and passenger vehicles, I would say, was built pre LLMs, pre-current wave of AI. And you know, Waymo essentially made it to market before, certainly started offering commercial um passenger rides before like GPT-3, for example. And so they probably weren't leveraging like the latest and greatest from Transformer World at that time, but obviously have been incorporating it since.

And I'm curious what like so if you're the difference is between um evolving a tech stack for autonomy that was built in twenty sixteen or twenty eighteen or twenty twenty. And then layering on whatever you can do today versus starting fresh today. Like what is the difference between those two?

Yeah, great question. So the the the landscape obviously has changed a lot. And again, if I go back to that twenty sixteen era, you know, this was even uh before ML had really taken off um in maths in at least autonomous vehicles. So you know, to stay between the lane lines, we might just actually be hand coding, look at these two different pixels. Is one yellow and is one not? That's where the lane line is. Like very, very like simple, you know, uh uh handcrafted kind of alg algorithms.

So so the whole space has evolved tremendously. And I think a lot of the companies have had to break down their stacks and and re engineer them um multiple times. And uh I'm sure Waymo I'm sure Waymo's had to do the same. But today, uh, I'll give you one example for for Humble, my company. Um, you know, we most of my most of my time in this technology space, we've been pretty wider heavy, like wide our first, I would say.

And uh even even for trucking on highway and there's there's been attempts to develop these like very long range lidars that could see, you know, three hundred, four hundred meters so you can handle the stopping distance of a truck.

The lidar technology for a long time was really good. And you can it was a little challenging to make it like robust and reliable and at scale, but but the technology itself was very good. And cameras kind of lagged behind. Like we weren't doing so much with the vision side of it.

Um today for me that at Humboldt, we flip that and we do a lot more on vision algorithms, we're camera first. And that's because of just the evolution of this technology has just changed so much. Um where now you get all this intelligence kind of would say for free, but there's you know, when I take an open source, uh, you know, the the the corollary to an L L M is a V L M, like a vision a vision language a visual language model.

And if I take a off the shelf VLM, something that understands an image and tells me what's in it, it's very, very good. Like there's a lot of intelligence baked in there. Um and and so I think that every company kind of has to kind of rethink their stacks as the technology evolves. What What really hasn't changed that much though is some of the validation that you do, some of the safety engineering that you do, the evolution of the hardware technology, because that's gotten a lot more robust.

Um so when you start a new effort now, you're kind of using a pretty different technical approach for the the brain, the AI, but you're using a lot of very well understood techniques for the rest of it, for how you develop a safe system. That's evolved tremendously in 10 years. Um big center right um. For those who aren't already familiar, what what are these vision language models, these VLMs that you referred to? Like what what is it and what does it actually enable?

Yeah, so so a VLM is like a LLM corollary is one the way I think about it. And it's taking an image as an input and providing some interpretation of what that image is is is happening in that image. And uh it's it's not something that really I'm I I had used in my past. Like this is very new to me also when when we started Humble. And our our head of autonomy, Drew Gray, um has been really, really in depth in it in the in the VLM space.

But what what I've seen coming out of it, it's like what I think a lot of people experience now. Like if you go to Chat GPT and you upload an image, right? And you say, Hey, what's going on in this image? It has a pretty good understanding of what's going on in that image. Um, and uh sometimes you will find intelligence baked in there or some, you know. Yeah.

I guess intelligence is like a hotly debated concept here right now, but but bear with me. Like it's some understanding of the image that goes beyond there's just a dog in here. It's like There's a dog that may have come from that door on the left or, you know, this construction cone is sitting on a pickup truck, not on the highway, and therefore is probably not an important construction element because it's just being carried by a truck, just to give an example of an edge case.

Um and so so the VLM brings some of that understanding uh right from the jump. And that That's really cool. Like pretty novel. Like I mean, when I started 10 years ago, like nothing like this existed. And so you had no Like you had to sort of like code in all the intelligence, like really try to understand what the features were. You know, we would take imagery or ladder data, we would send it to get labeled, people would put boxes. I'm sure you've seen images of boxes around it that say like

Dog or human or whatever, right? And then we would say, if you see a human, you probably want to do this kind of thing. I mean it's more complicated than that, but But we didn't get this this intelligence layer for free. Um and uh you know, there's open source technology out there that is very, very good. Uh you you'll find uh you'll find

free VLMs or open source VLMs um that have a lot of intelligence just available, which is like kind of a also kind of a wild place to be. Uh so yeah, quite an evolution.

My understanding of the sort of like censored debate in autonomy world, at least for passenger vehicles, right, there's the like LiDAR, radar. fusion side, which seems to be Waymo does a little bit of everything. Then there's like Tesla, which is which is camera first and camera only, basically maybe potentially a little bit of radar. But as I think about it, so I can see how uh these VLMs as an extension or corollary to LLMs allow you to do a lot more with video.

And, you know, just like get further faster on camera data. But my understanding was always that um the limitations on camera for autonomy are more around like it can get obscured. in certain conditions and things like that. And that's where you want your lidar or whatever, which which doesn't have the same set of issues. Is your view like you can go camera only as a result of the VLMs? Or is it you can lean more heavily on camera, but you still want this sensor fusion approach?

I think especially for trucks and you know, given what I was talking about earlier with this eighty thousand pound vehicle that you might be moving on the road, you want it to be as safe as it can possibly be. And so, you know, in my mind it's not a it's not a dogmatic debate about camera or LIDAR. It's what's the best technology for the moment that makes us the safest. And for from my perspective, for a vehicle, a truck, for example, you put on the road,

you would want it to have camera, LIDAR, and radar to do a a level four, level four being, you know, driverless, to do a level four truck today. Um and the reason and and the reason I say that is because you want to be able to see the world in multiple ways. Uh It's but there's always a sensor doing the most heavy lifting. It's not sort of this like co-equal like democracy between the three sensors. It's usually like

some some sort of priority is put on some algorithms depending on what you're doing. Um LIDAR doesn't see traffic lights, right, very well, or it doesn't see the red, green. So you would can't you'd use camera primarily for that. Uh bolidar can see better at night, radar can see through weather in some cases. Um and so if you wanna make a safe product and trucking in particular, you wanna really take advantage of all those today.

A human and and when you think about the end state, you know, a human is is is effectively two two cameras, right? Um two eyes, two cameras, and they're able to navigate the world. uh fairly well. Um and so you could make the argument that over time trucks would go to a vision only system. But I think that the the the debate, you know, sometimes you see around like Tesla and and and Waymo and others, it's feels a little dogmatic.

I think most of us on the trucking side have taken just approach that. Hey, the our margin for error is very low here. It's a very heavy vehicle. We have to be extremely safe. So we just put as much as a very good thing. equipment as we can to sort of try to guarantee that safety and and get very creative on the algorithm side and how to take all that data from the three different modalities and put them together.

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So I I I think of Humble as having at least two things that are kind of new and different in this space. One is just it to some extent it's like timing. You're starting fresh now. And so you get to like build from the ground up using VLMs and these things that didn't exist before and and benefiting from all the learnings that we've seen on pasture autonomy and so on. The other is your the form factor, the vehicle. So you mentioned that most of the attempts in autonomous trucking have been

you know, attaching a bunch of sensors to an existing truck, which is also, by the way, how it's been in mostly historically in passenger autonomy, right? Like that's what Wimo's doing on these these uh these Jaguar vehicles and then these other ones. Tesla maybe is a little different with the Robo Taxi, but those aren't really out on the market yet. So so that is similar. You are are taking a clean sheet approach and building a vehicle that doesn't even have a cab. Um

I guess in the in the long arc of history, of course that's gonna how it's it's gonna end up, right? When we don't need a driver, we shouldn't have a space in a driver for a vehicle. But apart from that, Give me the the thinking that led you to building a new vehicle. Yeah. So uh right at Humboldt we have this this cabless autonomous electric class eight truck, right? And

You know, the the the thinking that got me here was is a couple of things. It's kind of interesting. First I was like, okay, if you were to imagine that long arc of future like you're saying, what does that vehicle look like? What is the simplest possible vehicle to move for eight? And it's like a box with wheels.

Right, basically. So it's the it's a platform concept where where either a container is being loaded onto that platform or there maybe there's a or maybe it's just a box of the box truck moving. And that would that would be in theory the lowest possible cost of moving freight, right? It can't possibly get lower than that, I don't think. Maybe there's some new new mechanism to do it, at least for on road trucking.

So that's the first that was the first thought that got us here. And the second was like, Okay, is this possible today? Can we do this with the technology and where it is today? And, you know, that's where we started exploring it with Humble and the uh no, the answer the answer became like, yeah, this the technology is there. Like basically there's enough there's enough here where we can take that long arc of history and move it in a little bit, move it move it forward.

Um and then along the way, because you're doing a clean sheet design. you could think about all these problems that you run into into the space. Um so I'll give a I'll give a couple examples of of of what you can just rethink with this kind of vehicle. Uh so one way to think about our vehicle is that it combines a tractor and a trailer together into the single platform, right?

And uh a lot of challenges with doing this, by the way, so it's it's Right,'cause part of the market is like the tractor and the trailer are owned by different entities. Today, right? Some some it's not the entire market. Sometimes it's the same player, but you know, they get separated sometimes and sent off in different directions.

They get separated and sometimes for very good reasons. Like, you know, uh trailers are relatively inexpensive, you know, tractors are relatively expensive. So there there's a lot of like there's a lot of kind of interesting thinking around like how trying to combine this concept. Um but just from the technology side, for example.

If you've made the tractor smart, like like uh like with the other autonomous truck players, and you've left the trailer uh conventional or like a dumb trailer, quote unquote, right? Um you can't, for example, put sensors on the back of the trailer. Like you have a smart tractor, but you're just taking trailers from everywhere. So you can't see behind you. Okay. You can't see directly behind you. If you can't see directly behind you,

You cannot handle, for example, an accident where somebody just drives right into you. And I think that's there's maybe some clever ways to do that, but that's that's tricky. You cannot back into a dock, right? Because that requires

some amount of understanding of what's going on behind you. Um Uh one one interesting this is just like a kind of like an inside baseball thing, but one interesting challenge we've had in the industry is that trucks today, oh if they're if they're pulled over, they're required by law to deploy warning triangles.

And uh those warning triangles go behind the vehicle. If you only have made the tractor smart and the trailer has not been touched and you don't have a driver there, how do you deploy those warning triangles? And so

You know, companies like Aurora and I think Waymo when they were working on trucking, they they proposed using lights that are that are high up on the vehicle to indicate that the vehicle stalled as a replacement for the triangles. But there's advantages and disadvantages to that, right? And so it's it's being just being able to access the rear of the vehicle and have this full vision from a technology perspective just allows us kind of to do more. And what I was thinking about

What is the real future here for freight? Like again, sort of now a long arc, but what you would want is all freight to be fully automated, completely hands-off, nobody touching it. It goes to a warehouse, it loads up, it loads. goods from a a warehouse into that vehicle and drives his destination and onloads, right?

and completely hands off, no human. I think that's a that's that's where we want to get to. But to do that, you have to kind of treat the whole vehicle as smart, not just the tractor. And so that's how we got that's that's so it's kind of this interesting combination for us of the technology is ready.

the simplest concept that we can come up with for moving freight is a capitalist vehicle. And there's actually real structural technology advantages to doing it uh in the long term. And so that's that's that's where humble is today.

You mentioned your vehicle is is electric autonomous. Um There's this very interesting and very appealing direct correlation between autonomy and electrification that you see. Broadly, I presume you sort of knew from day one this was going to be an electric truck. But electric truck, I mean, setting aside autonomy even, it's got its own set of open questions on, of course, things like range and weight.

of the battery and charging infrastructure and charge time and so on. So how do you think about the electric component of your vehicle? Yeah. And I think it I think it starts with that um that vision that I talked about of like having fully hands off freight.

Uh if you were gonna have fully hands off freight, you would want it to be electric to charge to to handle the charging in an automated way. It's really hard to do that with diesel. Like how are you gonna get a diesel pump, you know, like into a I mean you could maybe do it with robots, that could be challenging. So so part of the electric story for me is just like how do you get to this fully automated freight vision?

So so electric is is is good from that perspective. There are challenges, charging, uh it forget the autonomy side, right? Electric trucks in the US have had a challenging rollout. They've been The electric trucks themselves have been fairly expensive, in some cases four or five hundred thousand dollars. A truck today, a tractor today is somewhere between one fifty and two fifty, depending on the

uh on on on what you're buying. The uh so tractor is uh a very expensive electric truck. There's charging infrastructure that needs to exist. Uh electric trucks are kind of having a moment again now'cause of the volatility in the world and some of the challenges that are going on. But

In general, it's been a tough rollout. But what we have seen in in in countries like China is that electric trucks are really taking off because the infrastructure developed. And once it's there and the costs are where they need to be, it makes a lot of sense.

It's tr it's t harder on the long haul. I think that's something that as an industry we have to reckon with a bit. You have to put a very large battery to do long haul. It is very heavy. You need a lot of power to charge. You need a lot of charging infrastructure. But for use cases that are more local, short haul, drayage, drayage is moving, freight out of out of ports, electric makes a lot of sense.

And so uh my you know, my career started in electrification. I worked um Bay Area was very big for electrification for a long time. Um that kind of moved out a little bit, but uh I I loved working on motors and batteries and and the technology there.

Uh so I I always, you know, in the back of my mind wanted to get back to it. And this was an opportunity for me because of that vision, that long-term vision, because it makes a lot of sense for kind of the short haul moves that we're aiming to do with Humble. Uh and you know, it's if like like I said, like electric trucks are having a moment. It is the technology that some countries have adopt have adopted en masse.

Um it just needs to be applied in the right way. And there's always gonna be challenges in tech rollout. Charging is certainly one of them, but they're solvable, they're all solvable.

Do you think you need to solve them? There's like a chicken or egg challenge often in things like this where it's like You need that charging infrastructure to be there in order for your customers to buy and utilize your truck. You don't necessarily want to be an EV charging company, I suspect. But somebody's got to do it. Um, and that there has to be enough of a demand signal from your customers such that somebody will

build the charging infrastructure and if it's third party owned charging infrastructure, make money on it, right? There's gotta be high enough utilization and so on. I think we're starting to see this happen. at ports and things like that to some extent where you've seen a little bit more electrification already. But is your view kind of like a a build it and they will come sort of a thing? If we build the vehicle, our customers will want the vehicle, charging will show up.

Or do you need to be more proactive? Yeah, I think it's a little bit of both. So so the so there has been quietly an industry built up on electric trucking. There are there are a few startups and companies out there that have been working on

depots and and and solving electric trucking and I think there's there's some been some shift to more short haul. Tesla semi obviously just I I think just rolled out of production, which is really great for the industry. And that'll that'll induce some charging efforts. Um So so it's it has been happening, it's just been happening relatively slowly, I would say, um, compared to what the industry expected. But I I feel like it's inevitable. And by you know, as Humboldt grows.

You know, my my my conversations with customers around this is we will help you solve it. It might not be that humble itself is developing technology around charging. We have we have our hands full with autonomy and and uh and a clean sheet design. There's a lot there, right? But but we will help the customer solve it because we were we we know everybody in the industry. We've been working with them for a long time and

And there's there's a myriad of solutions, right? You could do charging at the at the ports and the warehouses themselves. You can have depots. There's public infrastructure, private infrastructure.

Um but I think what we'll see is uh again, especially with what's going on in the world right now, I think we'll see we'll see a steady improvement in that and eventually you'll have you'll have real uptake on electric trucking because From a c cost structure perspective, once the charging is in place and you've sort of changed your operations and navigated that a little bit, it there's a lot of advantage to it.

What do you think the rollout of autonomo back to autonomous, sorry, not just electric, but what's the rollout of autonomous trucking gonna look like? Yeah, I I think people now have an intuition for what it looks like on the passenger side. It's sort of like a okay, Company X, usually Waymo, maybe it's gonna be Tesla soon, maybe it's gonna be Uber at some point, you know, says, okay, we're now offering publicly available rides in City X.

And uh it's ring fenced. You can only go, you know, within these boundaries. And they do that for a while and then they expand the boundaries and then they go to a new city and so on. So now we have a sense of like, here's what's coming in terms of passenger autonomy. Yeah I imagine it can't quite work the same. in trucking. So what's that what's that gonna look like? Paint me that picture.

Yeah. So so I'll I'll I'll put Humble aside for a second and just look at the industry as a whole. And you know, you have you have a number of very large players, um, very well capitalized, some public companies. all kind of going after the on road long haul autonomous trucking and they will they will continue to work on that and they will there will be you will see autonomous trucks on the highway. Um and I think you'll see them very soon and they will be driverless. Um

The all the all the sort of pieces have started to come into place like hardware and supply chain and regulatory efforts. Uh, you know, that took a while to sort of make sure state and federal uh regulators understood kind of what the technology and and how to deploy it. Um so those large players I think they will start deploying

Um, I mean traditionally they've been calling it a hub to hub model, right? Where it's like you sort of you can imagine at either end of a highway segment, you know, a destination for autonomous truck to go and and drop off rates. Sometimes you'll see it go right to customers.

I don't think you'll see generalized solutions where there's just like autonomous trucks zigzagging like everywhere for a while. But um I think what you'll see is some specific segments, mostly in Texas, where you'll you'll see occasional autonomous trucks and some scale applied there.

Um, that's for the long haul side. Uh at least in the in the space that the Humble plays in, um, for for class A trucking heavy haul and the short haul, there really hasn't been a whole lot of effort in that space yet. Um, so we're we're one of the first companies to tackle that.

Uh so you know, we'll see we'll see what our rollout looks like over time and how that goes. We're fairly young, we're less than a year, but we're moving very fast on that front. But I think you'll see you'll see long haul time strength.

moving. I think the question will shift to can we get a truck safely across the road in most cases? To can we handle the operational concerns? Can we handle the unit economics? Like that's a challenge. Um, you know, if you take a If you take a very expensive truck and then you make it significantly more expensive and then you know, then you're saying we've saved on some labor costs, you have to make that argument work really well.

I was going to ask you that question on unit economics. I mean, I I guess one way to get at it is like in a normal truck move, I'm this is gonna vary substantially, I'm sure, in terms of long haul versus short haul and other things, but like what portion of the fully loaded cost of delivery is the driver? You know, rem how how much savings do you get economically removing the driver? Yeah, so don't quote me, um, but about we use Atri, it's a it's an industry guide for for trucking costs.

And uh trucking cost in twenty six or twenty five looked at about two dollars and thirty, forty cents a a mile, at least for the long haul side. And I think the driver wages uh are about a dollar, a dollar ten of that uh per mile. So fairly significant.

Thirty, forty percent, something like that is the driver. So that's maybe if you're trying to save money and go autonomous, that's like the headroom you have to play with to make the vehicle more expensive. If you have to make the vehicle more expensive because you're adding sensors and things like that. Right. Yes, exactly. So it's like, you know, you have to you have to offset

that that labor reduction. Uh or you you you have some some room to play with there, but you know, you'll have some remote assistance. The vehicle will be a lot more expensive because of the sensors. There's no getting around that. Um a lot of the a lot of the uh current OEM efforts

to uh b basically the way it works a lot in industry now is that an OEM will make a will make a tractor um and uh we'll will partner with an autonomous provider to put the sensors on it and they try to do this at the factory. That's the goal.

But often they're doing often they're using like fairly expensive tractors, like the higher end models, because they have more room in the tractor for equipment. Um they call those sleepers where like a driver might sleep and they replace some of the like the bed with uh with computer, for example. Um so those vehicles are expensive. They become very expensive uh until they're at scale.

Uh so there's a challenge for sure in the unit economics. And I think like you even see that with Waymo's today, right? Like they have to get the unit economics down low enough to to make the the labor argument worth it. So I think that'll take time. That'll take time. And and part of the part of the story for Humboldt and the reason that that I started thinking about the lowest possible cost of moving free was the unit economic.

It's like well, if you remove a cab, you've taken out some significant cost from the vehicle. You've also taken out significant weight from the vehicle. And that allows us to kind of rethink the unit economics a little bit. Yeah, it strikes me that at least for a period of time. Uh Wamo is getting away with

inferior unit economics. Like they definitely have inferior unit economics. And I can tell you from personal experience, I'm sure you have too like I ride Wiimo's around even though they're more expensive than Ubers right now because it's cool and it's novel. And like Yeah. Uh I I doubt that same dynamic exists to the same extent in trucking. It's like j a classic thing of a B2C versus a B2B market.

I assume in trucking, in order for it to be adopted at any meaningful scale, maybe people will pilot something. But like I don't know why else they would do anything at scale unless they can save money. Yeah, I I think that's that's a real challenge. There's a real challenge in what you're saying. And it's very true. It's like in this B to B market when you're dealing with freight, you know, there's a safety component, there's a reliability component, like is my freight coming on time?

There is a but but ultimately, you know, it's the cost of moving freight and it has to be it has to be an advantage to a a shipper that's moving freight to want to use an autonomous service in some way. Um I'll give you I'll give you an example of a challenge that that the industry faces on the long haul side. You know, originally uh a lot of the ideas were build

you know, basically make a rail like I said. So you can imagine at the highway there's like a like a depot right at the highway and you would you would aggregate freight at this depot and an autonomous truck would take it You know, hundreds of miles, maybe a thousand miles, like a long distance, and drop off the freight at the other s at the other end of that that segment um at another depot.

And the thinking is like, yeah, we will do like these sort of short moves to the depots. Uh, and then an autonomous truck with its cost advantage structure would move the freight the long haul, and then you do these short moves again. Well the the challenge in that is

Today you don't have those depots and somebody has to build those depots and those depots are friction. Like who is moving the freight to that depot and why do they want to move it to that depot as opposed to just what they do today, which is just take it from their warehouse to the other end.

And so you can see that like some of the I think the economics here are tough and in this industry in particular, the economics matter a lot. Um, so I I think Waymo has managed the cool factor and, you know, people are willing to pay more and I think there is an experience component to it, right? I think people sometimes say they prefer Waymo's for the experience. Um, I think Waymo's did an excellent job with the interior and the experience, right?

But uh so I think they they have a little bit of an advantage there. I don't see that as much in freight. Like it's hard to Like what's a premium service in Freight? I mean, one example I I mean to give the counter argument, you know, you could you could say, Okay, this truck could go day and night, right? There's no restriction on like uh

uh how often that vehicle can maybe there's like some argument there, but in general, in general, like yeah, you have to get the cost structure down. Um part of the reason I started humble in a way is like I was just really thinking about the customers, what they need, like what their challenges are, and how to just get the cost of freight to be as as as well and meaningful as possible.

I guess final question for you. Um, what's the regulatory landscape like? Like what do you uh you know, are we allowed to run driverless vehicles on And I guess is it um is it tied to are you on a city street or in a drayage situation versus a highway and are those regulated differently or is trucking regulated as one category?

Yeah, that's a great question. So the regul the regulatory landscape is interesting and fun. Um I actually kind of like really um enjoy this part of the industry and I I love talking to regulators about it'cause I kinda feel like You want it's we're all breaking new ground, the regulators and the industry, and it's good to do that hand in hand and and have good dialogue on it. Um you know, the the situation today uh is there's

There, you know, we we work with NHTSA, that's a that's a major uh regulator for the trucking industry. We work with the FMCSA, that's another regulator for the trucking industry on the federal level. There's state laws that are that are state by state. Um, you know, a lot of the testing for autonomous trucks has happened in Texas because the regulatory landscape there has been favorable to autonomous trucks.

Uh in California a week ago you were you would not have been legally permitted to do a driverless truck and today you are. So there was some legislation uh or some new rulemaking there um that that allows for it with with certain conditions. Uh so so it's an evolving landscape. Um the you know for us developing uh this capitalist vehicle, you know, it's it's

It's got a sort of additional regulatory challenge in that you you're changing what the truck looks like, right? There's no steering wheel, there's no there's no windshield, right? Windshield is required by law. So how do you navigate that? So the way that works is that we talk to the regulators about what we're trying to do. Um, and we come up with a good plan for how do we do this, how do we test it to be safe.

Uh our vehicle our vehicle looks both like a tractor and a trailer. Like it has it has in some ways like it could you could think of it as like a smart trailer that just drives around by itself, right?

So if it's a smart trailer, how do you regulate a smart trailer versus a smart truck? Right. There's a lot of questions like that that we just work with the regulators on. Um but uh you know the I would say the the the regulators in general in this space have been very um very good to work with and

You know, everybody kind of sees where where where the technology is going and they just want to make sure that it's done in the safest way possible and, you know, thoughtfully, safely. Um and uh uh there's also, you know, this other component the regulators are thinking about, which is

what's happening around the world. Like who, you know, we see actually a lot of driverless efforts deploying in places like China, right? So are we being competitive in that in that regard while also being safe? Uh But yeah, it's a, it's, it's an it's an interesting question about the regulatory side. Actually, a really fun one to kind of kind of figure out hand in hand with them. All right, y'all. Thank you so much for doing this. Super interesting. Thanks for having me.

Ayal Cohen is the founder and CEO of Humble Robotics. This show is a production of Latitude Media. You can head over to latitudmedia.com for links to today's topic. This episode is produced by Max Savage Levinson, mixing and theme song by Sean Marquand. Anne Bailey edits the video version of the show. Stephen Lacey is our executive editor. I'm Shale Khan, and this is Catalyst.