The Future of AVs: Self-Driving Cars Explained  November 13, 2025

 

What's up everybody, Coy Wire here with a special edition of CNN 10. Today we're taking a deep dive into the world of artificial intelligence and self-driving cars.

 

Today we're going to Curiosity Lab in Peachtree Corners, Georgia, to experience this tech firsthand.

 

This is my first time in a Waymo. Let's go. You could call this one of the most advanced smart cities in the world.

 

Tomorrow's technologies being tested and created today. The color printer was invented here in Technology Park. The Hayes modem too.

 

modem [ˈmodəm] n. abbr.= modulator-demodulator 數據機

 

Now autonomous or self-driving vehicles are being steered to new frontiers. Air package delivery systems via drones. Mobile delivery robots tested and perfected.

 

Where are we? What is this place? I feel like I stepped into the future. This is Curiosity Lab. We are a non-profit just inside the city of Peachtree Corners.

 

What we do is we help companies test and deploy their technology on public infrastructure. That doesn't always sound super cool, but it is. I mean, think about all the stuff that public infrastructure entails, right? Roadways, intersections, even airspace.

 

entail [ɪnˋtel] v. 必需；使承担; 牵涉

airspace [ˋɛr͵spes] n. 上空；空间；领空

 

A lot of different technologies work on those things.

 

That's very important because we're living at a time where we're seeing more and more of it, hearing more and more about it. It might be taxicabs that are flying through this city.

 

taxicab [ˋtæksɪ͵kæb] n. 計程車

 

How well do you help companies prepare us for that type of future?

 

So when it comes to an environment, what is the ideal environment for testing? So you always start in a closed environment, right? There's no things coming in in terms of variables.

 

variable [ˋvɛrɪəb!] n.【数】变数

 

You want to make sure the product works. So in the case of a vehicle on a roadway, that would be like a closed track.

 

But we also know that from there, how do you get into an urban environment? How do you get into a real city?

 

And you've got to have that middle ground. So we have a closed three-mile loop inside a 500-acre ecosystem so that cars, technology, drones, whatever it is, can test in a real environment where there's real pedestrians, real cars, real people, real intersections.

 

middle ground 中间地带; 中间立场; 中间观点

 

So you can start to get the data and learn how these technologies work in real time with real elements so that you know, hey, we're ready to get into the city.

 

I just saw a robot fly by. I don't know what it was, but it was fast.

 

Oh my gosh, I think it might have been Gita. She's a cute little thing. Basically, she's a helping hand, essentially. She is a robot that follows a subject in front of it.

 

So it's not a self-driving one. It's not like it's doing delivery, but it's more like a robotic dog that follows you everywhere.

 

You don't need to carry a backpack anymore.

 

It's exactly what it is. It's a rolling robotic backpack. You open up that inside of it and they have different inserts.

 

rolling [ˋrolɪŋ] adj. 滚动的

 

I mean, you can make it follow you like a tailgate. But it also increases accessibility for things like disabled folk or even elderly and walkable communities if you're at the airport and you need help carrying stuff. So it's cool.

 

tailgate [ˋtel͵get] n.（车辆的）后拦板，后挡板；尾门，后车盖

walkable [ˋwɔkəb!] adj. 适于步行的；可以走去的

 

The fun fact there is that its design was based off of Joy from Star Wars. So they're quite cute, I think.

 

base off: base on; base off of

 

Now you're speaking my language.

 

Where's my lightsaber? I feel cars whizzing behind me. So tell me what's happening here. What are we seeing? What are we learning from what we're seeing?

 

whiz [hwɪz] v. 飕飕作声；飕飕掠过；急驰

 

Yeah, absolutely. So we talk about the roadway. That is a very loaded thing to think about. There's so many things going on at all different times on the roadway.

 

loaded [ˋlodɪd] adj. 装满的

 

And as drivers, we learn to get used to these things. You learn when someone's going to cut in front of you. You learn how to interact with different lights and different signals and different signs.

 

You know, what we're doing here is we're using cameras and we're putting analytics over those cameras to show you what's happening in here. So this can be a form of AI, right? So it could be doing things like object detection. As you can see here, it's looking at vehicle, vehicle.

 

It could clock up a bicyclist or a pedestrian, which we're seeing a couple of pedestrians come right there. So it says unknown and that's a part of testing, right? Is that it's still learning. It says person now as it's getting closer to the camera.

 

clock [klɑk] v.【口】（用机械装置）记录（时间，速度等）

 

But that's part of it, right? Is there are times where a truck comes through and it might say person and you're like, well, that's definitely not a person, but that's why you need the testing environment so they can train their AI models to do better.

 

Okay. So we've spoken about the cities, the roadways, the intersections of tomorrow.

 

Also, there will be the cars of tomorrow that work better with that. And I understand there's a garage where we can maybe check out when these cars put me to work. All right, let's do it.

 

Let's go. The company testing out their fleet of autonomous vehicles at Curiosity Lab during our visit is called May Mobility. These cars use similar technology to the brands we may be familiar with like Waymo.

 

But this company is particularly interested in making AVs that are more accessible for passengers who use wheelchairs, scooters, or need other accommodations.

 

accommodation [ə͵kɑməˋdeʃən] n. 特殊安排; 特殊措施; 特殊调整

 

In order for an autonomous vehicle to work, you have to have a bunch of different technology, right?

 

So you've got to have the hardware, and I'll walk through that in a minute, and you have to have the software, which is pretty much the brains of the technology.

 

So the AI component, you're using human-like reasoning, which is basically the software component and combining it with all the things you're gathering from the hardware so that the technology can make thousands and thousands and thousands of scenarios and decisions in real time.

 

So you'll see here different technologies. A lot of people say this looks like a cup holder. It is not.

 

cup holder 置杯座；置杯架

 

It's actually technology. You'll see cameras here and Lidar sensors. We have a total of nine cameras all around the vehicle, and then we have five Lidars and radars.

 

The other big guy here, the top hat, is basically our largest Lidar, and that is able to look out further away so that we can see what's happening in real time.

 

While autonomous vehicles are relatively new, Lidar has actually been around for quite some time. It was developed in the 1960s, and it was actually used on the Apollo space missions to map out the surface of the moon.

 

It uses lasers, shoots them out everywhere to measure distances and create an incredibly accurate picture of an environment. Here's how it works. The system fires millions of laser pulses, pew, pew, pew, every second in every direction.

 

They bounce off surrounding objects to create a detailed 3D picture of the surroundings. That includes everything from buildings to other cars, people, and animals.

 

It's similar in a way to echolocation, the system used by bats, whales, and dolphins to navigate and to hunt prey.

 

echolocation [͵ɛkoloˋkeʃən] n.【物】回波定位（法）

 

But this system swaps the sound waves for light. You may have seen the rapidly spinning mechanisms on some of these autonomous cars. Well, that allows them to have a 360-degree field of view to help eliminate blind spots and safely navigate the world around them.

 

Pop quiz, hot shot, self-driving cars often use Lidar to scan surroundings.

 

What does Lidar stand for?

 

Light detection and ranging, laser identification and radar, light identification and response, looking into dangers around the route.

 

Answer is light detection and ranging.

 

Lidar is a remote sensing method used to examine the surface of the earth.

 

So what you want to do is you want to use a combination of historical data, right, which is accumulated over time based on different locations. So for example, let's say you're in Georgia, hot weather, right? You're in Phoenix, Arizona, hot but dry weather, and you're in Michigan where you have snow.

 

So you want to be able to take all of those elements and have the vehicle learn from all the different weather conditions so that when it's a location, if we happen to get snow in Georgia this year, the vehicle will know what to do.

 

But I think about, you know, my daughters when they're old enough to be going places, I think that I would feel comfortable with them being in a vehicle all to themselves.

 

The tech is only going to get better, right? And you would think as there are more and more autonomous vehicles on the roadways that are now communicating with each other, they're like computer brains communicating with other drivers.

 

And so you would think that would be even safer than kind of guessing and wondering what a human might do.

 

There's a lot of transparency and visibility into a vehicle. You have cameras everywhere, and so you can see what's happening.

 

And so for them, in a lot of ways, they're probably a lot safer, you know, in the vehicle. We all know that, you know, last year I think there were over 40,000 deaths in the U.S. from accidents, road accidents. That's things like, you know, falling asleep, texting and driving, intoxication.

 

intoxication [ɪn͵tɑksəˋkeʃən] n. 醉酒

 

So all of those things can happen, you know, with your child, right, for the future. So I would argue that for the future, and maybe even today, that these vehicles are, you know, safe and hopefully that's their future. And then you've got to think too, there's others as well.

 

I mean, you have kids, right? But there's people with disabilities, great for them. And then, you know, people who are elderly, right, they can come in and use those vehicles. In Minnesota, we have one of our biggest groups of riders are seniors and the middle school kids.

 

Not seniors in high school. No, seniors. And middle schoolers.

 

And middle schoolers because, you know, a lot of times they don't have a way to get home, you know, after after-school activities. And so this is a way for them to do it safely.

 

What do you think? I want you to press pause for a moment, discuss with your friends.

 

If a self-driving car service was widely available in your city or town, maybe they already are, would you use them? Would you trust AI over getting your own driver's license? What are the risks? What are the benefits?

 

Thanks for taking a ride with me today on this special edition of CNN 10. I learned a lot today. I hope you did too.

 

Be kind, stay curious, and rise up.