Chris Gerdes: The future race car -- 150mph, and no driver

63,313 views ・ 2012-07-11

TED


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Translator: Morton Bast Reviewer: Thu-Huong Ha
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So, how many of you have ever
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gotten behind the wheel of a car
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when you really shouldn't have been driving?
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Maybe you're out on the road for a long day,
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and you just wanted to get home.
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You were tired, but you felt you could drive a few more miles.
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Maybe you thought,
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I've had less to drink than everybody else,
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I should be the one to go home.
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Or maybe your mind was just entirely elsewhere.
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Does this sound familiar to you?
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Now, in those situations, wouldn't it be great
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if there was a button on your dashboard
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that you could push, and the car would get you home safely?
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Now, that's been the promise of the self-driving car,
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the autonomous vehicle, and it's been the dream
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since at least 1939, when General Motors showcased
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this idea at their Futurama booth at the World's Fair.
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Now, it's been one of those dreams
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that's always seemed about 20 years in the future.
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Now, two weeks ago, that dream took a step forward,
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when the state of Nevada granted Google's self-driving car
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the very first license for an autonomous vehicle,
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clearly establishing that it's legal for them
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to test it on the roads in Nevada.
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Now, California's considering similar legislation,
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and this would make sure that the autonomous car
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is not one of those things that has to stay in Vegas.
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(Laughter)
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Now, in my lab at Stanford, we've been working on
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autonomous cars too, but with a slightly different spin
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on things. You see, we've been developing robotic race cars,
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cars that can actually push themselves to the very limits
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of physical performance.
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Now, why would we want to do such a thing?
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Well, there's two really good reasons for this.
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First, we believe that before people turn over control
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to an autonomous car, that autonomous car should be
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at least as good as the very best human drivers.
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Now, if you're like me, and the other 70 percent of the population
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who know that we are above-average drivers,
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you understand that's a very high bar.
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There's another reason as well.
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Just like race car drivers can use all of the friction
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between the tire and the road,
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all of the car's capabilities to go as fast as possible,
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we want to use all of those capabilities to avoid
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any accident we can.
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Now, you may push the car to the limits
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not because you're driving too fast,
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but because you've hit an icy patch of road,
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conditions have changed.
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In those situations, we want a car
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that is capable enough to avoid any accident
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that can physically be avoided.
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I must confess, there's kind of a third motivation as well.
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You see, I have a passion for racing.
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In the past, I've been a race car owner,
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a crew chief and a driving coach,
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although maybe not at the level that you're currently expecting.
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One of the things that we've developed in the lab --
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we've developed several vehicles --
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is what we believe is the world's first
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autonomously drifting car.
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It's another one of those categories
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where maybe there's not a lot of competition.
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(Laughter)
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But this is P1. It's an entirely student-built electric vehicle,
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which through using its rear-wheel drive
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and front-wheel steer-by-wire
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can drift around corners.
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It can get sideways like a rally car driver,
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always able to take the tightest curve,
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even on slippery, changing surfaces,
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never spinning out.
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We've also worked with Volkswagen Oracle,
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on Shelley, an autonomous race car that has raced
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at 150 miles an hour through the Bonneville Salt Flats,
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gone around Thunderhill Raceway Park in the sun,
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the wind and the rain,
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and navigated the 153 turns and 12.4 miles
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of the Pikes Peak Hill Climb route
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in Colorado with nobody at the wheel.
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(Laughter)
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(Applause)
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I guess it goes without saying that we've had a lot of fun
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doing this.
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But in fact, there's something else that we've developed
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in the process of developing these autonomous cars.
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We have developed a tremendous appreciation
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for the capabilities of human race car drivers.
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As we've looked at the question of how well do these cars perform,
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we wanted to compare them to our human counterparts.
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And we discovered their human counterparts are amazing.
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Now, we can take a map of a race track,
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we can take a mathematical model of a car,
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and with some iteration, we can actually find
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the fastest way around that track.
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We line that up with data that we record
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from a professional driver,
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and the resemblance is absolutely remarkable.
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Yes, there are subtle differences here,
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but the human race car driver is able to go out
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and drive an amazingly fast line,
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without the benefit of an algorithm that compares
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the trade-off between going as fast as possible
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in this corner, and shaving a little bit of time
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off of the straight over here.
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Not only that, they're able to do it lap
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after lap after lap.
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They're able to go out and consistently do this,
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pushing the car to the limits every single time.
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It's extraordinary to watch.
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You put them in a new car,
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and after a few laps, they've found the fastest line in that car,
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and they're off to the races.
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It really makes you think,
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we'd love to know what's going on inside their brain.
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So as researchers, that's what we decided to find out.
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We decided to instrument not only the car,
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but also the race car driver,
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to try to get a glimpse into what was going on
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in their head as they were doing this.
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Now, this is Dr. Lene Harbott applying electrodes
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to the head of John Morton.
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John Morton is a former Can-Am and IMSA driver,
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who's also a class champion at Le Mans.
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Fantastic driver, and very willing to put up with graduate students
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and this sort of research.
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She's putting electrodes on his head
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so that we can monitor the electrical activity
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in John's brain as he races around the track.
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Now, clearly we're not going to put a couple of electrodes on his head
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and understand exactly what all of his thoughts are on the track.
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However, neuroscientists have identified certain patterns
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that let us tease out some very important aspects of this.
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For instance, the resting brain
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tends to generate a lot of alpha waves.
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In contrast, theta waves are associated with
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a lot of cognitive activity, like visual processing,
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things where the driver is thinking quite a bit.
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Now, we can measure this,
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and we can look at the relative power
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between the theta waves and the alpha waves.
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This gives us a measure of mental workload,
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how much the driver is actually challenged cognitively
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at any point along the track.
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Now, we wanted to see if we could actually record this
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on the track, so we headed down south to Laguna Seca.
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Laguna Seca is a legendary raceway
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about halfway between Salinas and Monterey.
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It has a curve there called the Corkscrew.
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Now, the Corkscrew is a chicane, followed by a quick
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right-handed turn as the road drops three stories.
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Now, the strategy for driving this as explained to me was,
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you aim for the bush in the distance,
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and as the road falls away, you realize it was actually the top of a tree.
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All right, so thanks to the Revs Program at Stanford,
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we were able to take John there
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and put him behind the wheel
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of a 1960 Porsche Abarth Carrera.
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Life is way too short for boring cars.
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So, here you see John on the track,
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he's going up the hill -- Oh! Somebody liked that --
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and you can see, actually, his mental workload
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-- measuring here in the red bar --
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you can see his actions as he approaches.
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Now watch, he has to downshift.
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And then he has to turn left.
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Look for the tree, and down.
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Not surprisingly, you can see this is a pretty challenging task.
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You can see his mental workload spike as he goes through this,
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as you would expect with something that requires
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this level of complexity.
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But what's really interesting is to look at areas of the track
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where his mental workload doesn't increase.
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I'm going to take you around now
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to the other side of the track.
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Turn three. And John's going to go into that corner
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and the rear end of the car is going to begin to slide out.
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He's going to have to correct for that with steering.
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So watch as John does this here.
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Watch the mental workload, and watch the steering.
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The car begins to slide out, dramatic maneuver to correct it,
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and no change whatsoever in the mental workload.
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Not a challenging task.
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In fact, entirely reflexive.
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Now, our data processing on this is still preliminary,
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but it really seems that these phenomenal feats
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that the race car drivers are performing
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are instinctive.
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They are things that they have simply learned to do.
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It requires very little mental workload
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for them to perform these amazing feats.
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And their actions are fantastic.
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This is exactly what you want to do on the steering wheel
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to catch the car in this situation.
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Now, this has given us tremendous insight
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and inspiration for our own autonomous vehicles.
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We've started to ask the question:
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Can we make them a little less algorithmic
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and a little more intuitive?
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Can we take this reflexive action
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that we see from the very best race car drivers,
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introduce it to our cars,
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and maybe even into a system that could
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get onto your car in the future?
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That would take us a long step
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along the road to autonomous vehicles
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that drive as well as the best humans.
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But it's made us think a little bit more deeply as well.
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Do we want something more from our car
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than to simply be a chauffeur?
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Do we want our car to perhaps be a partner, a coach,
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someone that can use their understanding of the situation
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to help us reach our potential?
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Can, in fact, the technology not simply replace humans,
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but allow us to reach the level of reflex and intuition
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that we're all capable of?
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So, as we move forward into this technological future,
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I want you to just pause and think of that for a moment.
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What is the ideal balance of human and machine?
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And as we think about that,
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let's take inspiration
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from the absolutely amazing capabilities
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of the human body and the human mind.
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Thank you.
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(Applause)
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