needs to know what's around it. Based on these factors, it needs to be able to make smart

and safe driving decisions in the real world. And once you get in the car, you start to

get a real feel for the way the technology works and what it's like in real driving situations.

So there are a few things that have to happen before the car can start safely drive itself.

First, it has to figure out its location in the world. So we use GPS, but GPS isn't always

that accurate, which is why we rely on our other sensors, like the laser, which picks

up on details in the environment that help us identify a more precise location.

So think of the sensors as the car's eyes and ears. But with eyes that can see far off

into the distance and 360 degrees around the car. And the great thing about having all

of these sensors is that they can talk to each other and get cross-checked information

about the environment. So while we take in a ton of information using our sensors, it's

our software that really processes all this and differentiates between objects.

All these objects are visible on the laptop that the safety drivers use while testing the vehicles.

Based on what the vehicle senses and processes, these objects will be represented by different

colored boxes. Cyclists will be red, pedestrians yellow, and the vehicles will appear as either

green or pink. These boxes demonstrate the processing that takes place within the software.

And think about the complexity here. People look different, cars have different shapes

and sizes. Yet despite these nuances, the software needs to classify these objects appropriately

based on factors like their shape, movement pattern, or location.

For example, if there's a cyclist in the bike lane, the vehicle understands that this is

a cyclist, not another object like a car or a pedestrian, so the cyclist appears as a

red box on the safety driver's laptop. And the software can also detect the cyclist's

hand signal and yield to them appropriately. When our engineers think about where the car

should drive and how, safety is always the top priority. So the vehicle takes into account

many things, like how close it is to other objects, or matching speed with traffic, or

anticipating other cars cutting in. For example, as a passenger, it can feel a

little uncomfortable passing by a large vehicle on the road. Our engineers have taught the

software to detect the large vehicles and the laptop shows them as larger boxes on screen.

As our vehicle passes by a large truck, it will actually keep to the farther side of

the lane and give ourselves a little bit more space. And, we've also taught the vehicle

to recognize and navigate through construction zones. The vehicle's sensors can spot the

orange signs and cones early to alert the car of any lane blockage ahead, and then we

can change lanes safely. Another thing that's really important is for

the vehicle to drive in a naturalistic way, because when it's natural, and the car abides

by social norms on the road, it's also safer. For example, at four-way stops, people typically

rely on eye contact to communicate whose turn it is. And in our case, the vehicle inches

forward into the intersection to indicate its intent.

So, my role as a safety driver is first and foremost to keep the car, myself, and everyone

around me safe. And in addition to keeping the car safe, I also provide detailed feedback

to the developers and let them know if the car does anything that maybe I wouldn't have

done personally. Maybe the car wasn't assertive enough in a lane change, or wasn't fast enough

at a green light. We provide the detailed feedback so they can fine-tune the whole driving

experience. By getting out there and driving in the real

world, we're getting a better understanding of what exactly it's going to take to improve

the safety and comfort and ease of transportation. And that's really what our project's all about.