CNN10 Special Edition: The Future of AVs: Self-Driving Cars Explained | November 13, 2025

[00:12] What's up everybody? Koiwire here with a

[00:14] special edition of CNN 10. Today we're

[00:16] taking a deep dive into the world of

[00:18] artificial intelligence and self-driving

[00:20] cars. Today we're going to Curiosity Lab

[00:23] in Peach Tree Corners, Georgia to

[00:25] experience this tech firsthand. This is

[00:27] my first time in a Whimo. Let's go.

[00:31] You could call this one of the most

[00:32] advanced smart cities in the world.

[00:35] Tomorrow's technologies being tested and

[00:37] created today. The color printer was

[00:40] invented here in Technology Park. The

[00:42] Haze modem, too. Now, autonomous or

[00:45] self-driving vehicles are being steered

[00:48] to new frontiers. Air package delivery

[00:51] systems via drones. Mobile delivery

[00:54] robots tested and perfected. Where are

[00:57] we? What is this place? I feel like I

[00:59] stepped into the future.

[01:00] >> This is Curiosity Lab. We are a

[01:02] nonprofit just inside the city of Peach

[01:04] Tree Corners. And what we do is we help

[01:06] companies test and deploy their

[01:08] technology on public infrastructure. So

[01:10] that meant always sounds super cool, but

[01:12] it is. I mean, think about all the stuff

[01:14] that public infrastructure entails,

[01:16] right? Roadways, intersections, even

[01:18] airspace. Um, a lot of different

[01:19] technologies work on those things.

[01:21] >> And that's very important because we're

[01:22] living at a time where we're seeing more

[01:23] and more of it, hearing more and more

[01:25] about it. They might be taxi cabs that

[01:28] are flying through this city. So how

[01:31] well all do you help companies prepare

[01:33] us for that type of future?

[01:34] >> Sure. So when it comes to an environment

[01:37] like what is the ideal environment for

[01:38] testing? So you always start in a closed

[01:40] environment, right? There's there's no

[01:42] things coming in in terms of variables.

[01:43] You want to make sure the product works.

[01:45] So in the case of a vehicle on a

[01:46] roadway, that would be like a closed

[01:48] track. But we also know that from there,

[01:50] how do you get into an urban

[01:51] environment? How do you get into a real

[01:53] city? And you've got to have that middle

[01:55] ground. We have a closed three mile loop

[01:57] inside a 500 acre ecosystem so that

[02:00] cars, technology, drones, whatever it

[02:02] is, can test in a real environment where

[02:04] there's real pedestrians, real cars,

[02:06] real people, real intersections. So you

[02:08] can start to get the data and learn how

[02:10] these technologies work in real time

[02:12] with real elements so that you know,

[02:13] hey, we're ready to get into the city.

[02:15] >> I just saw a robot fly by. I don't know

[02:18] what it was, but

[02:19] >> oh my gosh, I think it might have been

[02:20] Cheetah. She's a cute little thing.

[02:22] Basically, she's a helping hand

[02:24] essentially. She is a a robot that

[02:26] follows a subject in front of it. So,

[02:27] it's not a self-driving one. It's not

[02:29] like it's doing delivery, but it's more

[02:31] like, you know, a robotic dog that

[02:32] follows you everywhere.

[02:33] >> You don't need to carry a backpack

[02:34] anymore.

[02:34] >> It's exactly what it is. It's a rolling

[02:36] robotic backpack. You open up the uh vat

[02:39] inside of it, and you know, they have

[02:40] different inserts. I mean, you can make

[02:41] it follow you like a tailgate. Um, but,

[02:43] you know, it also increases

[02:44] accessibility for things like disabled

[02:47] folk or even elderly and, you know,

[02:49] walkable communities if you're at the

[02:50] airport and you need help carrying

[02:52] stuff. Um, so it's cool. The fun fact

[02:54] there is that its design was based off

[02:57] of the droids in Star Wars. So they're

[02:59] they're quite cute, I think.

[03:01] >> Now you're speaking my language. Where's

[03:04] my lightsaber? I feel cars whizzing

[03:06] behind me. So tell me what's happening

[03:08] here. What are we seeing? What are we

[03:09] learning from what we're seeing?

[03:11] >> Yeah, absolutely. So we talk about, you

[03:13] know, the roadway. Um that is a very

[03:16] loaded thing to think about. There's so

[03:18] many things going on at all different

[03:19] times on the roadway. And as drivers,

[03:21] you know, we learn to get used to these

[03:23] things. You learn when someone's going

[03:24] to cut in front of you. You learn how to

[03:26] interact with different lights and

[03:28] different signals and different signs.

[03:29] You know, what we're doing here is we're

[03:30] using uh cameras and we're putting

[03:32] analytics over those cameras to show you

[03:34] what's happening in here. So, um this

[03:36] can be a forum of AI, right? So, it

[03:38] could be doing things like object

[03:39] detection. As you can see here, it's

[03:41] looking at vehicle vehicle. It could

[03:42] clock a, you know, a bicyclist or a

[03:45] pedestrian, which we're seeing a couple

[03:46] pedestrians come right there. So, it

[03:49] says unknown and that's a part of

[03:51] testing, right? Is that, you know, it's

[03:52] still learning. It says person now as

[03:54] it's getting closer to the camera.

[03:56] >> Um, but that's part of it, right? Is

[03:57] there are times where a truck comes

[03:58] through and it and you know, it might

[04:00] say person and you're like, well, that's

[04:01] definitely not a person. But that's why

[04:03] you need the testing environment so they

[04:04] can train their AI models to do better.

[04:06] >> Okay. So, we've spoken about the cities,

[04:08] the roadways, the intersections of

[04:10] tomorrow.

[04:12] Also, there will be the cars of tomorrow

[04:14] that work better with that. And I

[04:16] understand there's a garage where we can

[04:18] maybe check out one of these cars. Put

[04:19] me to work.

[04:20] >> All right, let's do it. Let's go.

[04:22] >> The company testing out their fleet of

[04:24] autonomous vehicles at Curiosity Lab

[04:26] during our visit is called May Mobility.

[04:29] These cars use similar technology to the

[04:31] brands we may be familiar with like

[04:33] Whimo. But this company is particularly

[04:35] interested in making AVs that are more

[04:38] accessible for passengers who use

[04:40] wheelchairs, scooters, or need other

[04:42] accommodations.

[04:43] >> In order for an autonomous vehicle to

[04:45] work, you have to have a bunch of

[04:47] different technology, right? So, you've

[04:49] got to have the hardware, and I'll walk

[04:51] through that in a minute. And you have

[04:52] to have the software, which is pretty

[04:54] much the brains of the technology. So

[04:56] the AI component, you're using

[04:58] human-like reasoning, which is basically

[05:01] the software component, and combining it

[05:03] with all the things you're gathering

[05:04] from the hardware so that the technology

[05:07] can make thousands and thousands and

[05:09] thousands of scenarios and decisions in

[05:11] real time.

[05:12] >> Mhm.

[05:13] >> So you'll see here different

[05:15] technologies. A lot of people say this

[05:16] looks like a cup holder. It is not. It's

[05:20] actually technology.

[05:22] And you'll see cameras here and LAR

[05:24] sensors. We have a total of nine cameras

[05:27] all around the vehicle. And then we have

[05:29] five LARs and radars. The other big guy

[05:32] here, the top hat, is basically um our

[05:35] largest LAR. And that is able to look

[05:38] out further away so that we can see

[05:41] what's happening in real time.

[05:43] >> While autonomous vehicles are relatively

[05:46] new, lidar has actually been around for

[05:48] quite some time. It was developed in the

[05:50] 1960s and it was actually used on the

[05:53] Apollo space missions to map out the

[05:55] surface of the moon. It uses lasers,

[05:59] shoots them out everywhere to measure

[06:00] distances and create an incredibly

[06:02] accurate picture of an environment.

[06:05] Here's how it works. The system fires

[06:07] millions of laser pulses

[06:10] every second in every direction. They

[06:12] bounce off surrounding objects to create

[06:14] a detailed 3D picture of its

[06:16] surroundings. That includes everything

[06:18] from buildings to other cars, people,

[06:20] and animals. It's similar in a way to

[06:23] echolocation, the system used by bats,

[06:25] whales, and dolphins to navigate and to

[06:27] hunt prey. But this system swaps the

[06:30] sound waves for light. You may have seen

[06:32] the rapidly spinning mechanisms on some

[06:34] of these autonomous cars. Well, that

[06:36] allows them to have a 360° field of view

[06:40] to help eliminate blind spots and safely

[06:42] navigate the world around them.

[06:45] Pop quiz hot shot. Self-driving cars

[06:48] often use lidar to scan surroundings.

[06:50] What does lidar stand for? Light

[06:51] detection and ranging. Laser

[06:53] identification and radar. Light

[06:55] identification and response. Looking

[06:57] into dangers around the route. Answer is

[07:00] light detection and ranging. Lidar is a

[07:03] remote sensing method used to examine

[07:05] the surface of the earth. So what you

[07:08] want to do is you want to use a

[07:10] combination of historical data, right,

[07:12] which it's accumulated over time based

[07:15] on different locations. So for example,

[07:18] let's say you're in Georgia, hot

[07:20] weather, right? You're in Phoenix,

[07:24] Arizona, hot but dry weather, and you're

[07:27] in Michigan where you have snow. So, you

[07:30] want to be able to take all of those

[07:32] elements and have the vehicle learn from

[07:34] all the different weather conditions so

[07:36] that when it's a location, if we happen

[07:38] to get snow in Georgia this year, the

[07:41] vehicle will know what to do.

[07:43] >> But I think about, you know, my

[07:45] daughters when they're old enough to be

[07:48] going places,

[07:50] I think that I would feel comfortable

[07:51] with them being in a vehicle all to

[07:54] themselves. The tech is only going to

[07:56] get better, right? And you would think

[07:58] as there are more and more autonomous

[08:00] vehicles on the roadways that are now

[08:03] communicating with each other, they're

[08:05] like computer brains communicating with

[08:07] other drivers. And so you would think

[08:10] that would be even safer than kind of

[08:13] guessing and wondering what a human

[08:15] might do.

[08:16] >> There's a lot of um transparency and

[08:19] visibility into a vehicle. you have

[08:21] cameras everywhere and um so you you can

[08:25] see what's happening and so for them in

[08:28] a lot of ways they're probably a lot

[08:30] safer you know in the vehicle we all

[08:32] know that you know last year I think

[08:35] there were over 40,000 deaths in the US

[08:38] from um accidents road accidents it's

[08:41] things like you know falling asleep

[08:43] texting and driving intoxication so all

[08:46] of those things can happen you know with

[08:49] with your

[08:50] right for the future. So, and I would

[08:53] argue that for the future and maybe even

[08:55] today that these vehicles are for, you

[08:57] know, safe and hopefully that's their

[08:59] future. And then you've got to think

[09:01] too, there's others as well. I mean, you

[09:03] have kids, right? But there's um people

[09:06] with disabilities, great for them. And

[09:09] then, you know, people who are elderly,

[09:11] right? They can come in and use those

[09:12] vehicles. In um Minnesota, we have um

[09:16] one of our biggest groups of riders are

[09:19] seniors and the middle school kids

[09:22] because they

[09:23] >> not seniors in high school.

[09:24] >> No, senior citizens. Yes, that's senior

[09:26] middle schoolers and middle schoolers

[09:28] because you know a lot of times they

[09:30] don't have a way to get home um you know

[09:33] after after school activities and so

[09:36] this is a way for them to do it safely.

[09:38] >> What do you think? I want you to press

[09:40] pause for a moment. Discuss with your

[09:41] friends if a self-driving car service

[09:44] was widely available in your city or

[09:45] town. Maybe they already are. Would you

[09:47] use them? Would you trust AI over

[09:49] getting your own driver's license? What

[09:51] are the risks? What are the benefits?

[09:53] Thanks for taking a ride with me today

[09:54] on this special edition of CNN 10. I

[09:56] learned a lot today. I hope you did,

[09:58] too. Be kind, stay curious, and rise up.