Nearly 100 years ago, a Czech physician and novelist by the name of Miles J. Breuer predicted the future.
In his 1930 science fiction book Paradise and Iron, Breuer “invented” the concept of autonomous vehicles, offering up this idea of a mysterious paradise island where all the cars, trucks, and boats drove themselves.
Ninety years later, his dream is turning into a reality…
Semi-autonomous cars are on the roads today, conducting test drives in various cities throughout the world, including Phoenix, Detroit, Boston, Berlin, London, and many, many more.
Fully autonomous cars are not too far behind. Indeed, in China, fully autonomous vehicles without any driver in the car are already being tested.
In the not-too-distant future, these semi-autonomous and fully autonomous cars will go into production mode and end up in the garages of consumers all across the globe.
Worldwide, about 70 million new passenger cars are sold every year. In 2020, only 8 million of those cars sold will have some level of low autonomy.
By 2030, all 70 million are expected to include some form of autonomy, with many projecting to have high autonomy.
This is a disruption like no other. Which is why we cover it in Innovation Investor – our exclusive subscription-only service for small- to mid-cap growth investors – with an entire megatrend devoted to Next-Gen Mobility stocks.
The entire multi-trillion-dollar auto market is on the cusp of being uprooted by autonomous vehicle (AV) technology.
What’s the best way to play this emerging Self-Driving Revolution?
By investing in the core technology making all of it possible: LiDAR.
There’s a weird distinction here, that I need to be clear about…
I’m referring to what is and what isn’t considered controversial…
On the one hand, saying that self-driving cars will become ubiquitous by 2030 is not controversial.
On the other hand, saying LiDAR is key to unlocking the technological capabilities of the self-driving revolution is controversial.
We have Elon Musk to thank for that.
Here’s the story:
To unlock full autonomy is to enable cars to have “complete vision.” Basically, it means cars need a human-like ability to see and respond to their surroundings.
Ideally, you want to do this with built-in cameras, since cameras are space- and cost-efficient on the hardware front.
But computer vision (which is what you get from cameras) has significant limitations which have proven difficult to overcome, so it’s commonplace across the AV space to equip cars with add-on, laser-light perception sensors called LiDAR.
The nitty gritty science and engineering behind LiDAR are complex, but the idea is digestible at a high level.
Here’s how it works:
LiDAR sensors beam out lasers to their surroundings. Those laser beams hit objects around the car and then bounce back to the sensors. The sensors then either carefully measure the travel time of those laser pulses (called time-of-flight) or a change in frequency of the returning light wave (called Frequency Modulated Continuous Wave) to create a proxy for distance.
Do this thousands of times in a 360-degree frame-of-view and – voila – you have a dynamic “picture” of the surrounding environment.
Across the AV space, the commonly accepted idea of the self-driving car of the future is one that includes cameras, LiDAR, and RADAR, for redundancy purposes. LiDAR being the principal element of the stack since it provides the highest-resolution picture of objects in the immediate vicinity of a car.
But Tesla’s visionary CEO Elon Musk does not conform to this accepted thinking. Instead, he believes that the future of self-driving is “vision only” – or just cameras, no LiDAR or RADAR.
The logic is simple. A human can drive a car with just two eyes and a brain. Why can’t a machine drive a car with a few cameras and a robust AI processor?
At some point in the future, maybe. But today? It won’t happen.
To understand why, let’s talk science.
So, the human eye is a really good camera. It’s said to have resolution on par with a 600-megapixel camera. Tesla, though, is using 1.2-megapixel cameras.
The human eye has a dynamic, 360-degree frame-of-view. Cameras, however, have a limited field of vision.
So, for autonomous vehicles to “see” with the resolution and frame-of-view comparable to a human eye, it would need dozens upon dozens of cameras strapped to it. That’s expensive, that’s bulky, and that’s simply not a very scalable solution.
Meanwhile, even if you do that, you have to deal with the problem of CV data density.
CV data is very rich, very complex, and very messy. Each pixel contains a ton of unstructured data. Processing all that data takes a ton of work. Now, multiply all that data across dozens of cameras, and you’re creating a problem that is incredibly difficult for AI to tackle – let alone quickly enough for self-driving, where a minuscule delay in processing and responses means life or death.
In other words, for “vision-only” autonomy to really work at scale, you would need some huge advancements in both hardware and software capability – the likes of which my connections working in the AV industry say are very, very unlikely to happen anytime soon.
How does LiDAR solve this problem?
LiDAR uses short-wavelength laser beams to create a very high-resolution picture with a wide frame-of-review. The result is that two LiDAR sensors can do what dozens of cameras would be able to do…
At the same time, LiDAR data is low-density. It’s structured, 3D position data (X, Y, Z) with time. That data is very easy to process, meaning you don’t need an impossibly complex software system to make sense of LiDAR data. It’s very straightforward.
To be sure, LiDAR sensors are awfully expensive. That’s why Elon is so anti-LiDAR. Back when Tesla started its self-driving efforts in the early 2010s, LiDAR sensors cost as much as $75,000 per sensor!
But the cost of LiDAR has plunged in recent years, thanks to Wright’s Law and certain technological improvements. Today, some companies are making LiDAR sensors for less than $1,000 – while most experts see those prices coming down toward $100 within the decade.
So now that LiDAR produces high-res, easy-to-digest data and the cost of the sensors are plunging to compete with the cost of cameras and RADAR… why won’t LiDAR be the core foundational technology of the self-driving revolution?
It will be – LiDAR is the future of self-driving.
Specifically, the self-driving car of the future will include cameras (for color data), LiDAR (for high-res, near-field perception), and RADAR (for long-range perception in inclement weather); and in that sensor suite, LiDAR will be the most valuable and most important.
So… I repeat… the best way to play the self-driving revolution is to buy LiDAR stocks.
And in the world of LiDAR stocks, there is one clear leader – one company that is just miles ahead of everyone else. A potential juggernaut in the automotive technology industry over the next decade.
This is easily a $100-plus BILLION company in the making. Yet, it’s current market capitalization is less than $10 billion.
Yep, this is a potential 10X investment opportunity.
And the time to buy is right now.
To get the name, ticker symbol, and key business details of this and other potential 10X opportunities, click here to watch my Exponential Growth Summit and subscribe to my venture-capital-style research platform, Innovation Investor.
Trust me, you do not want to miss this stock pick. Otherwise, you will be kicking yourself in 2025.
On the date of publication, Luke Lango did not have (either directly or indirectly) any positions in the securities mentioned in this article.
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