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00:00
Translator: Morton Bast
Reviewer: Thu-Huong Ha
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翻译人员: Ling Jin
校对人员: Kelvin Wang
00:15
So, how many of you have ever
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你们当中有多少人
00:17
gotten behind the wheel of a car
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当你不应该开车的时候
00:18
when you really shouldn't have been driving?
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还开车跟在另一部车后面?
00:24
Maybe you're out on the road for a long day,
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有可能你已经开了一整天的车
00:26
and you just wanted to get home.
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心里只想回家
00:27
You were tired, but you felt you could drive a few more miles.
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你已经身心疲惫了,但你感觉还能再驾驶多几英里
00:30
Maybe you thought,
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大概你有想过
00:31
I've had less to drink than everybody else,
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我喝得没有其他人多
00:33
I should be the one to go home.
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我可以驾车回家
00:35
Or maybe your mind was just entirely elsewhere.
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或者也许你的大脑已经在神游
00:40
Does this sound familiar to you?
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这些你们听起来有点熟悉吧?
00:41
Now, in those situations, wouldn't it be great
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现在,在这些情况下
00:44
if there was a button on your dashboard
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如果仪表盘上有一个按钮
00:46
that you could push, and the car would get you home safely?
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你按一下,车就可以带你安安全全地回家,会不会很棒
00:52
Now, that's been the promise of the self-driving car,
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如今,这些都是自动汽车能做到的
00:54
the autonomous vehicle, and it's been the dream
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自动汽车从 1939 年通用汽车公司在世
00:57
since at least 1939, when General Motors showcased
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通用汽车公司在世界展销会上展示他们未来汽车的的理念
01:00
this idea at their Futurama booth at the World's Fair.
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就一直是一个梦想
01:03
Now, it's been one of those dreams
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现在,它已成为那些看起来
01:05
that's always seemed about 20 years in the future.
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总是还要再等20年的梦想之一
01:10
Now, two weeks ago, that dream took a step forward,
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两个星期前,这个梦想有了突破
01:12
when the state of Nevada granted Google's self-driving car
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当内华达州授予谷歌的自驾汽车
01:15
the very first license for an autonomous vehicle,
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第一个无人驾驶的上路许可证,
01:19
clearly establishing that it's legal for them
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明确地表示他们在内华达州道路上
01:21
to test it on the roads in Nevada.
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测试是合法的
01:23
Now, California's considering similar legislation,
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现在,加州的也正在考虑类似的立法,
01:27
and this would make sure that the autonomous car
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这将确保无人驾驶汽车
01:29
is not one of those things that has to stay in Vegas.
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不会像赌博这类事一样只会发生在拉斯维加斯。
01:32
(Laughter)
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(笑声)
01:34
Now, in my lab at Stanford, we've been working on
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现在,在我在斯坦福大学的实验室里,我们也一直在
01:38
autonomous cars too, but with a slightly different spin
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研究无人驾驶汽车,但在对事物研究的理念上略有不同
01:42
on things. You see, we've been developing robotic race cars,
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我们一直在开发机器人赛车
01:46
cars that can actually push themselves to the very limits
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它们在性能上可以
01:50
of physical performance.
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到达其物理极限
01:52
Now, why would we want to do such a thing?
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那么为什么我们想要做这样的事呢?
01:55
Well, there's two really good reasons for this.
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嗯,有两个好的理由来解释
01:57
First, we believe that before people turn over control
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第一,我们认为在人完全将控制交给
02:01
to an autonomous car, that autonomous car should be
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一部无人驾驶汽车之前,这部无人驾驶汽车
02:04
at least as good as the very best human drivers.
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至少得运行得像一位好的驾驶员一样
02:07
Now, if you're like me, and the other 70 percent of the population
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那么,如果你像我,还有那其他70%的人一样
02:10
who know that we are above-average drivers,
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认为我们是高于平均水平的司机
02:12
you understand that's a very high bar.
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你明白我们高估了自己
02:16
There's another reason as well.
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同时还有另一个原因
02:18
Just like race car drivers can use all of the friction
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就像赛车手可以利用
02:22
between the tire and the road,
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车胎和路面间所有的摩擦
02:23
all of the car's capabilities to go as fast as possible,
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还有汽车的最大性能来尽可能快的开一样
02:26
we want to use all of those capabilities to avoid
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我们想用这些性能来避免
02:29
any accident we can.
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任何我们可以避免的交通事故
02:31
Now, you may push the car to the limits
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现在,你可能把车开到极限
02:33
not because you're driving too fast,
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并不是说你开得太快
02:35
but because you've hit an icy patch of road,
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而是说你开到有冰的路面上了
02:37
conditions have changed.
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路况变了
02:39
In those situations, we want a car
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在这些情况下,我们希望这部汽车
02:42
that is capable enough to avoid any accident
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有能力避免任何那些
02:45
that can physically be avoided.
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人工可以避免的意外
02:48
I must confess, there's kind of a third motivation as well.
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我必须承认,还有第三个理由
02:52
You see, I have a passion for racing.
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你瞧,我对赛车很痴迷
02:55
In the past, I've been a race car owner,
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过去,我曾拥有一部赛车
02:57
a crew chief and a driving coach,
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是一个车队的头,也是驾校教练
03:00
although maybe not at the level that you're currently expecting.
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虽然也许水平没有你期待得那么高
03:04
One of the things that we've developed in the lab --
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我们在实验室中做的几件事中的一件--
03:06
we've developed several vehicles --
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就是我们开发了几部车--
03:08
is what we believe is the world's first
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我们相信他们是世界上
03:10
autonomously drifting car.
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第一步无人漂移汽车
03:13
It's another one of those categories
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它是无人车中新的分类
03:15
where maybe there's not a lot of competition.
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也许它还没有竞争对手
03:18
(Laughter)
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(笑声)
03:19
But this is P1. It's an entirely student-built electric vehicle,
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我们叫它P1。它是一部完全由学生设计的
03:23
which through using its rear-wheel drive
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后轮驱动电动车
03:25
and front-wheel steer-by-wire
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线控方向盘
03:27
can drift around corners.
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可以在拐角漂移
03:29
It can get sideways like a rally car driver,
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它能像一个汽车拉力赛选手一样从路边过
03:31
always able to take the tightest curve,
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也从能转过急弯
03:33
even on slippery, changing surfaces,
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即使在湿滑,不断变化的路面
03:36
never spinning out.
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也从来不会打滑被甩出去
03:37
We've also worked with Volkswagen Oracle,
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我们也曾与大众 Oracle合作出研发
03:40
on Shelley, an autonomous race car that has raced
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一部叫” 谢莉“的无人驾驶赛车
03:43
at 150 miles an hour through the Bonneville Salt Flats,
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它能用每小时 150 英里的速度沿着邦纳维尔盐滩行驶
03:46
gone around Thunderhill Raceway Park in the sun,
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能在阳关明媚时,能在大风大雨天
03:51
the wind and the rain,
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跑在 Thunderhill 赛车跑道上
03:53
and navigated the 153 turns and 12.4 miles
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并在Pikes Peak Hill Climb 线路上
03:58
of the Pikes Peak Hill Climb route
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开12.4英里,通过153拐弯处
04:00
in Colorado with nobody at the wheel.
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这是在科罗拉多州,真的一个人都没在车上
04:03
(Laughter)
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(笑声)
04:05
(Applause)
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(掌声)
04:10
I guess it goes without saying that we've had a lot of fun
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我想我们不用说
04:14
doing this.
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这样做真的有很多乐趣
04:15
But in fact, there's something else that we've developed
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但事实上,我们还研发了一些其它的东西
04:19
in the process of developing these autonomous cars.
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在这个研发无人驾驶汽车的过程中
04:22
We have developed a tremendous appreciation
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我们对人类赛车手的能力
04:26
for the capabilities of human race car drivers.
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变的更加的的钦佩
04:29
As we've looked at the question of how well do these cars perform,
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当我们想这些车可以运作的多好时候
04:34
we wanted to compare them to our human counterparts.
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我们想把无人驾驶车和人类驾驶的操作做一个比较
04:37
And we discovered their human counterparts are amazing.
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我们发现执行任务的人类是不可思议的
04:43
Now, we can take a map of a race track,
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现在,我们可以拿一张赛车跑道图
04:47
we can take a mathematical model of a car,
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我们可以做一个数字模型车
04:49
and with some iteration, we can actually find
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加上一些迭代,我们可以找到
04:52
the fastest way around that track.
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整个跑道的最快路径
04:54
We line that up with data that we record
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我们把一个职业赛车手开车数据记录下来
04:56
from a professional driver,
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进行直线图表分析
04:58
and the resemblance is absolutely remarkable.
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相似度是那样的惊人
05:02
Yes, there are subtle differences here,
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是的,这里还是有细微的差别的
05:05
but the human race car driver is able to go out
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赛车手能够在户外
05:08
and drive an amazingly fast line,
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开到最快的那条线路
05:10
without the benefit of an algorithm that compares
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而不用计算程序去比较
05:13
the trade-off between going as fast as possible
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是该在这个拐弯出开快点
05:15
in this corner, and shaving a little bit of time
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还是应该在开过这个
05:17
off of the straight over here.
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直线的时候减点速
05:19
Not only that, they're able to do it lap
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不但如此,他们能如此地开一圈
05:23
after lap after lap.
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一圈又一圈
05:25
They're able to go out and consistently do this,
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他们能在户外,持续地这么做
05:28
pushing the car to the limits every single time.
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每一次都把车用到极限
05:32
It's extraordinary to watch.
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看起来真的不可思议
05:35
You put them in a new car,
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你给他们换部车
05:37
and after a few laps, they've found the fastest line in that car,
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在跑几个圈后他们就已经能找到适合车的最快的路线
05:41
and they're off to the races.
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接着,他们就可以比赛了
05:45
It really makes you think,
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这不禁使你想
05:46
we'd love to know what's going on inside their brain.
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我们真的很想知道他们大脑里究竟发生了什么
05:51
So as researchers, that's what we decided to find out.
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作为研究人员说,这就是我们决定要挖据的
05:56
We decided to instrument not only the car,
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我们决定测量不仅仅是车
05:58
but also the race car driver,
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还有赛车手
06:00
to try to get a glimpse into what was going on
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尝试去了解在他们赛车时候
06:03
in their head as they were doing this.
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他们大脑的变化
06:05
Now, this is Dr. Lene Harbott applying electrodes
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现在,这是 琳恩·哈博特博士把电极片
06:09
to the head of John Morton.
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放在约翰 · 莫顿的头上的照片
06:10
John Morton is a former Can-Am and IMSA driver,
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约翰 · 莫顿是前Can-Am 和IMSA的赛车手
06:13
who's also a class champion at Le Mans.
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他也是勒芒赛事上出类拔萃的冠军
06:15
Fantastic driver, and very willing to put up with graduate students
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极棒的赛车手,并且愿意忍受研究生
06:18
and this sort of research.
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和这类的研究
06:20
She's putting electrodes on his head
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她把电极片放在他的头上
06:23
so that we can monitor the electrical activity
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这样,我们可以监测当约翰绕着轨道飚车时候
06:25
in John's brain as he races around the track.
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他大脑电波的活动
06:28
Now, clearly we're not going to put a couple of electrodes on his head
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显然我们不是放一对电极片在他头上
06:31
and understand exactly what all of his thoughts are on the track.
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就可以准确的了解到他在跑道上飚车时候所有的想法
06:34
However, neuroscientists have identified certain patterns
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然而,神经学家已经可以识别了一定的模式
06:38
that let us tease out some very important aspects of this.
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让我们对这个研究中一些非常重要的因素能理出头绪
06:42
For instance, the resting brain
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例如,休息中的大脑
06:43
tends to generate a lot of alpha waves.
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往往会产生大量的α波
06:46
In contrast, theta waves are associated with
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与此相反,θ波与大量认知活动
06:49
a lot of cognitive activity, like visual processing,
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相关联,如视觉处理
06:53
things where the driver is thinking quite a bit.
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赛车手正在想的事,很多
06:56
Now, we can measure this,
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现在,我们可以测量这一点
06:57
and we can look at the relative power
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我们可以看到
06:59
between the theta waves and the alpha waves.
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θ波与α波之间的相对动力
07:01
This gives us a measure of mental workload,
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这给我们了脑力负荷的一个测试
07:04
how much the driver is actually challenged cognitively
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在轨道上任何一个地方,赛车手实际上
07:07
at any point along the track.
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需要接受多少认知上的挑战
07:09
Now, we wanted to see if we could actually record this
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现在,我们想看看我们是否能真实地在跑道上
07:12
on the track, so we headed down south to Laguna Seca.
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记录这点,所以我们向南出发去卡赛道
07:15
Laguna Seca is a legendary raceway
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卡赛道是有传奇色彩的赛道
07:17
about halfway between Salinas and Monterey.
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大约在萨利纳斯和蒙特雷的中间
07:20
It has a curve there called the Corkscrew.
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它有一道弯被称为瓶塞钻
07:22
Now, the Corkscrew is a chicane, followed by a quick
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现在,这个瓶塞钻是一个S 形弯道
07:24
right-handed turn as the road drops three stories.
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接下来是一个很急的右转弯与此同时路面好像下陷3层楼那么高
07:27
Now, the strategy for driving this as explained to me was,
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现在,可以理解这个驾驶的策略为
07:31
you aim for the bush in the distance,
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你以远处的灌木丛为目标
07:33
and as the road falls away, you realize it was actually the top of a tree.
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当你感到跑道向下落的时候,你才意识到你其实是在树尖上
07:36
All right, so thanks to the Revs Program at Stanford,
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很好,非常感谢斯坦福大学的自驾车研究项目
07:39
we were able to take John there
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我们把约翰带到哪里了
07:41
and put him behind the wheel
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让他 主宰1960年
07:42
of a 1960 Porsche Abarth Carrera.
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保时捷的阿巴特卡雷拉的方向盘
07:44
Life is way too short for boring cars.
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大家对一般的车的喜好就像昙花一现一样
07:48
So, here you see John on the track,
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所以,在这里你看到约翰在赛道上
07:50
he's going up the hill -- Oh! Somebody liked that --
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他在爬坡, 哦 !有人也喜欢来这里飚车 — —
07:52
and you can see, actually, his mental workload
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实际上,你可以看到一条红的长方形条
07:54
-- measuring here in the red bar --
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正在监测他的脑力负荷--
07:56
you can see his actions as he approaches.
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随着他的移动,你可以看到他的反映
07:59
Now watch, he has to downshift.
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现在看看,他不得不换到低档。
08:02
And then he has to turn left.
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然后他必须左转。
08:03
Look for the tree, and down.
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看清楚路旁的树,然后下坡。
08:07
Not surprisingly, you can see this is a pretty challenging task.
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没什么可大惊小怪的,您可以看到这是一个非常有挑战性的任务
08:09
You can see his mental workload spike as he goes through this,
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你可以看到当他经历这一切的时候,他的大脑负荷增加了
08:12
as you would expect with something that requires
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你会预测到
08:15
this level of complexity.
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这种复杂程度会产生的事
08:17
But what's really interesting is to look at areas of the track
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但是真正有趣的事是看
08:21
where his mental workload doesn't increase.
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不会使他脑力负荷增加的一些赛道的区域
08:24
I'm going to take you around now
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我将带你绕到
08:25
to the other side of the track.
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赛道的另外一半
08:26
Turn three. And John's going to go into that corner
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数三下,约翰将开到拐角
08:29
and the rear end of the car is going to begin to slide out.
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汽车的尾部将会滑出轨道
08:31
He's going to have to correct for that with steering.
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他将不得不打方向盘使车回到轨道
08:33
So watch as John does this here.
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所以看好约翰是怎么操作的
08:35
Watch the mental workload, and watch the steering.
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看看他的脑负荷,和方向盘
08:38
The car begins to slide out, dramatic maneuver to correct it,
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赛车开始滑出去了,戏剧性的操作使它回到轨道上了,
08:41
and no change whatsoever in the mental workload.
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而大脑负荷却丝毫没有变化
08:45
Not a challenging task.
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这不是一个具有挑战性的任务
08:48
In fact, entirely reflexive.
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实际上,完全是条件的放射
08:51
Now, our data processing on this is still preliminary,
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现在,我们对此的数据处理仍是初步的阶段
08:55
but it really seems that these phenomenal feats
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但这现象明显表明
08:57
that the race car drivers are performing
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这些赛车手表现出来的惊人水平
08:59
are instinctive.
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是其本能
09:01
They are things that they have simply learned to do.
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这些事对他们来说孰能生巧了
09:04
It requires very little mental workload
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对他们来说完成这样了不起的事
09:06
for them to perform these amazing feats.
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只需要很少的大脑负荷。
09:09
And their actions are fantastic.
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他们表现真的很棒
09:12
This is exactly what you want to do on the steering wheel
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当车遇到这种情况时候
09:15
to catch the car in this situation.
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你想做到的就是去控制好车
09:18
Now, this has given us tremendous insight
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现在,这给我们的无人驾驶汽车的研究
09:22
and inspiration for our own autonomous vehicles.
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有了巨大的启示和灵感
09:25
We've started to ask the question:
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我们已经开始问自己
09:27
Can we make them a little less algorithmic
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我们可以使我们的自驾车少一点计算程序
09:29
and a little more intuitive?
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而多一点直觉性的东西吗?
09:31
Can we take this reflexive action
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我们能借助
09:34
that we see from the very best race car drivers,
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我们现在从最好赛车手身上看到的这种对条件反射的反应
09:36
introduce it to our cars,
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从而把它运用到我们的车上吗
09:38
and maybe even into a system that could
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再或者运用到你们
09:40
get onto your car in the future?
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未来车子的系统里?
09:42
That would take us a long step
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我们还需要很大的努力
09:43
along the road to autonomous vehicles
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来研制出和最棒的车手一样的
09:46
that drive as well as the best humans.
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无人驾驶汽车
09:48
But it's made us think a little bit more deeply as well.
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它同时使我们从更深的层面去思考
09:51
Do we want something more from our car
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我们想让我们的车为我们做得更多
09:54
than to simply be a chauffeur?
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而不是简简单单地一个驾驶员吗?
09:56
Do we want our car to perhaps be a partner, a coach,
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我们想让我们的车成我们的伙伴,教练
10:00
someone that can use their understanding of the situation
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或者是能了解到周围环境的那个人
10:03
to help us reach our potential?
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从而帮助我们发挥我们的潜力吗?
10:08
Can, in fact, the technology not simply replace humans,
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那么科技能不能不只是简单的取代人类
10:10
but allow us to reach the level of reflex and intuition
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而且可以让我们达到
10:14
that we're all capable of?
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我们都能达到的直觉的反应水平?
10:18
So, as we move forward into this technological future,
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所以,当我们向这个科技时代迈进的时候
10:20
I want you to just pause and think of that for a moment.
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我想你停下来思考一会
10:23
What is the ideal balance of human and machine?
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什么是人类和机器之间最理想的平衡
10:26
And as we think about that,
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当我们思考时候
10:28
let's take inspiration
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让我们用
10:30
from the absolutely amazing capabilities
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人类身体和大脑的
10:33
of the human body and the human mind.
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了不起的能力来激发自己
10:36
Thank you.
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谢谢
10:38
(Applause)
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(掌声)
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