The two types of self-driving technology every investor should know about

VaselineOctober 6, 2024

0 5 minutes read

The two types of self-driving technology every investor should know about

Editor’s note: Tesla’s “Robotaxi” event on October 10 will mark the beginning of a new era for autonomous transportation. It is one that will have far-reaching implications throughout the economy.

By making autonomous vehicles a reality, Tesla opens the door to tectonic disruption and opens vast new opportunities. My fellow InvestorPlace Luke Lango he thinks he’s seen one of them, so I encourage you to tune in to his 10am show on Monday 7 October here.

Tomorrow’s AV technologies are about to penetrate today, and the change will be like nothing we’ve seen before. So, I’ve invited Luke here today to tell you more about those technologies… and to preview his show on October 7th.

My friends with kids in college now tell me that their kids grew up thinking they’d never have to drive because of self-driving cars.

My friends with kids in high school now tell me the same thing.

The people I know with middle schoolers though…those kids always did known should sign up for the driver.

Silicon Valley can only tell us that self-driving cars are “five years away from five years away” for so long before we doubt their story.

Still, I’ve been optimistic about autonomous vehicles for some time. After all, industry developments were promising.

And here’s the thing… May be those middle school kids now won’t have to learn to drive.

These self-driving technological developments are rapidly moving from promise to reality.

You probably know about the rapid expansion of autonomous transportation services in Phoenix and San Francisco. But did you know that Waymo has started offering driverless rides to people in Austin? today?

You may have heard about the rollout of self-driving cars in Texas and Arizona. But did you know that California Governor Gavin Newsom vetoed a bill that would have banned driverless trucks from his state’s roads on Monday?

And with the upcoming launch of Elon Musk’s robotaxi in just one week — Thursday, October 10 — I think the stage is set for self-driving cars to begin transforming the $11 trillion transportation services industry. (Sign up for my Oct. 7 morning show about that event — and how to position your portfolio to profit from it — going here.)

Now, this is all great information to know. But it doesn’t mean much if we don’t understand how these vehicles actually work.

After all, understanding the technology behind a burgeoning megatrend is the key…before it can even begin advantage from her.

So to potentially turn the ‘Age of Avs’ into a massive payday, we first need to understand how self-driving cars work…

A Sensory Trifecta

Essentially, a self-driving car is operated by a combination of sensors – the “hardware stack” – and AI-powered software – the “software stack”.

In short, the car’s sensors gather information about its surroundings. The AI software then processes that data to determine whether the vehicle should accelerate, brake, change lanes, turn, etc.

All of this must happen virtually instantaneously.

Typically, the hardware stack consists of three sensors: cameras, radarand lidar. A typical self-driving car uses all three sensors, as each has strengths and weaknesses that complement the others nicely.

Let’s go through them one by one…

Cameras collect visual data. They capture high-resolution images of the vehicle’s environment, similar to how your own eyes work. These cameras recognize different signs, lane markings and traffic lights – and can distinguish between different objects such as pedestrians, cyclists and vehicles. They are very good at providing detailed visual information that helps the car understand its surroundings. But they tend to perform poorly in poor visual environments, such as when there is poor light or inclement weather.
An AV radar sensors they emit radio waves that bounce off objects and return to the sensor, providing information about the distance, speed and movement of obstacles in the car’s vicinity. These sensors perform well in all weather conditions (complementing cameras nicely), but offer limited resolution and detail (where cameras excel).
Lidar – which stands for light detection and measurement – is essentially a radar powered by lasers. These sensors emit laser pulses that bounce off surrounding objects and return to the sensor. By measuring the time it takes for the light to return, the lidar can create a high-resolution 3D map of the vehicle’s environment. This provides accurate depth perception, allowing the machine to understand the exact shape, size and distance of surrounding objects. However, lidar does not capture color or texture information (as cameras do).

In other words, AVs use cameras to see things. The radar senses how fast those things are moving. And lidar helps calculate the exact position of these things.

In this sense, it is easy to see how these three sensors work together in a self-driving car.

The era of autonomous vehicles has arrived

Self-driving cars use what’s called “sensor fusion” to combine camera, radar and lidar data, creating a complete, accurate and reliable model of their environment.

For example, if a person crosses the road in front of an AV:

The camera identifies him as a person.
The radar tracks the pedestrian’s speed to predict potential collisions.
The lidar measures the exact distance, shape and movement of the pedestrian.

Together, these sensors allow the car to make informed decisions such as slowing down, stopping or redirecting, ensuring safe and efficient navigation.

But it can only make those decisions with the help of its software stack.

An AV uses a variety of software and methods to provide real-time information about the environment. There are essentially five components to this software stack: perception, location, prediction, planningand control.

In short:

The perception the software uses sensor fusion, object classification and semantic segmentation to create a comprehensive picture of a car’s environment.
The location the software uses highly detailed maps and location data to accurately place the car in its environment.
The prediction the software uses machine learning models to predict how things in the environment may act in different scenarios.
The planning the software takes the results of the perception, localization and prediction software to decide the optimal path for the car.
The control the software executes the planned action, controlling steering, acceleration, braking, etc.

Together, these hardware and software stacks create the technological background for self-driving cars.

The Final Word

Of course, each company approaches the self-driving problem differently. But this is the general framework that most follow.

As such, when looking to invest in the autonomous vehicle supply chain, it makes sense to look for stocks that supply the critical components of AVs..

Find the most powerful camera, radar and lidar suppliers. Focus on the most promising software games.

They will likely be the biggest winners in the Age of AVs.

In fact, if you’re hoping to position yourself for an era of AV-fueled market gains, click here to save your place for my special video briefing on Monday, October 7, 10 a.m. Eastern. There, we’ll talk all about the rapidly unfolding Age of AVs.

This upcoming broadcast aims to get you ready for Tesla’s Robotaxi launch later this week (which we expect to be huge). Although it is about much more than the upcoming debut.

Indeed, in this show, I’ll break down all the recent innovative developments in the autonomous vehicle industry, including how robotaxis are set to completely transform transportation, save millions of lives, and pocket up to $30,000 a year in passive income . .

Plus, I’ll show you how to get my handbook of the best AV stocks to buy right now.

Click here to book your place.

And see you there.

Sincerely,