PJ Vogt

Like you're trying to teach a machine by day.

Did it affect how you thought about human driving by night?

Almost obnoxiously so to any passengers in the car with me.

I was obsessed with one big question, which is why do humans drive the way they drive?

And it turns out there were no good answers.

And I still think they're not great answers.

And instead of actually answering that question, we've just turned to machine learning to infer the deep truths behind why humans do what they do.

And so there's some basic principles that you can understand.

Like we try to minimize lateral acceleration, meaning you don't want to be thrown to the outside of your car when you're making a turn.

So you're going to slow down.

But how much do you slow down, right?

And it turns out that's contextual.

Don gave me an example.

So you're trying to figure out the right speed and angle for the car on one of those tight, curvy on-ramps onto the highway.

You want it to feel comfortable for a passenger.

Don says you can work out the math.

The lateral acceleration is two meters per second squared.

But the surprising thing is that number only applies on the on-ramp.

If I put you at a cul-de-sac in a neighborhood and you were going to do a U-turn at the end of the cul-de-sac, even though the speed is significantly slower, if you did two meters per second squared of lateral acceleration around a cul-de-sac, you would tell your driver they were crazy.

It would be incredibly uncomfortable.