Jennifer Healey: If cars could talk, accidents might be avoidable

48,352 views ・ 2013-04-25

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00:00
Translator: Joseph Geni Reviewer: Morton Bast
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譯者: KA WAI WONG 審譯者: Emma Chiang
00:12
Let's face it:
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面對現實吧
00:14
Driving is dangerous.
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開車是危險的
00:17
It's one of the things that we don't like to think about,
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這是我們不願去想的事
00:20
but the fact that religious icons and good luck charms
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但現實中我們在世界各地看到
00:23
show up on dashboards around the world
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汽車儀器板上的宗教畫像和平安符
00:28
betrays the fact that we know this to be true.
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卻揭露我們其實知道開車危險
00:32
Car accidents are the leading cause of death
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車禍是美國16至19歲青年
00:36
in people ages 16 to 19 in the United States --
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死亡的主因
00:40
leading cause of death --
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車禍是導致死亡的主因
00:43
and 75 percent of these accidents have nothing to do
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而當中百分之七十五的車禍
00:47
with drugs or alcohol.
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和毒品或酒精無關
00:49
So what happens?
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到底發生了什麼?
00:51
No one can say for sure, but I remember my first accident.
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沒人能確實說出 我記得我第一次車禍
00:55
I was a young driver out on the highway,
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當時我還年輕 在高速公路上
00:59
and the car in front of me, I saw the brake lights go on.
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看到前面車輛的煞車燈亮了
01:02
I'm like, "Okay, all right, this guy is slowing down,
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我心想﹕好吧 這傢伙慢了下來
01:03
I'll slow down too."
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那我也跟著慢下來吧
01:05
I step on the brake.
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我跟著踩煞車
01:07
But no, this guy isn't slowing down.
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但我錯了 他不是減慢速度
01:09
This guy is stopping, dead stop, dead stop on the highway.
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而是停車 竟然在高速公路上停車
01:12
It was just going 65 -- to zero?
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從時速六十五英哩降到... 零?
01:15
I slammed on the brakes.
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我急踩剎車
01:16
I felt the ABS kick in, and the car is still going,
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ABS系統啟動了 但車仍向前駛
01:19
and it's not going to stop, and I know it's not going to stop,
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車繼續向前 我知道車不會停了
01:22
and the air bag deploys, the car is totaled,
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氣囊彈出 車子毀了
01:25
and fortunately, no one was hurt.
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幸好沒有傷亡
01:28
But I had no idea that car was stopping,
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我完全沒想到那輛車會停
01:32
and I think we can do a lot better than that.
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我認為我們可以做得更好
01:36
I think we can transform the driving experience
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我們可以透過讓車之間對話
01:40
by letting our cars talk to each other.
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改變駕駛的方式
01:44
I just want you to think a little bit
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大家想一想
01:46
about what the experience of driving is like now.
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現在我們是怎樣開車的
01:48
Get into your car. Close the door. You're in a glass bubble.
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上車 關上門 在一個玻璃安全室裡
01:53
You can't really directly sense the world around you.
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你無法直接感受周遭的世界
01:55
You're in this extended body.
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在這個擴大了的軀殼裡
01:58
You're tasked with navigating it down
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你的任務是
02:00
partially-seen roadways,
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在看不清路面的情況下
02:02
in and amongst other metal giants, at super-human speeds.
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在其他高速行駛的車輛間行駛
02:06
Okay? And all you have to guide you are your two eyes.
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只有你的眼睛能幫助你
02:11
Okay, so that's all you have,
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對 就只有你的眼睛
02:12
eyes that weren't really designed for this task,
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我們的眼睛不是用來完成這任務的
02:14
but then people ask you to do things like,
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可是人們總要求你做這樣的事
02:18
you want to make a lane change,
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例如你要換條車道
02:20
what's the first thing they ask you do?
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第一件要做的事是什麼?
02:22
Take your eyes off the road. That's right.
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不看路面的情況 是的
02:25
Stop looking where you're going, turn,
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不去看你前進的方向 然後轉彎
02:27
check your blind spot,
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檢查是不是有盲點
02:29
and drive down the road without looking where you're going.
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不看路 一直向前開
02:33
You and everyone else. This is the safe way to drive.
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在座各位和其他人 都會認為這是安全駕駛
02:36
Why do we do this? Because we have to,
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為什麼要這樣做? 因為我們必須
02:38
we have to make a choice, do I look here or do I look here?
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必須選擇 是要看這邊 還是那邊
02:40
What's more important?
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更重要的是甚麼?
02:42
And usually we do a fantastic job
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通常我們都能在路上
02:45
picking and choosing what we attend to on the road.
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好好挑選我們要走的路
02:48
But occasionally we miss something.
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但偶爾我們也會出小差池
02:52
Occasionally we sense something wrong or too late.
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有時候我們意識到做錯決定 已經太遲
02:57
In countless accidents, the driver says,
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無數的車禍 司機都說
02:59
"I didn't see it coming."
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沒看到有車駛過來
03:01
And I believe that. I believe that.
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我相信這種說法 非常相信
03:04
We can only watch so much.
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我們能看到的有限
03:07
But the technology exists now that can help us improve that.
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不過現今科技可以幫助我們
03:12
In the future, with cars exchanging data with each other,
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將來只要車輛間能互相交換資訊
03:17
we will be able to see not just three cars ahead
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我們不僅可以看到前面三部輛車
03:20
and three cars behind, to the right and left,
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還能看到後面三輛車 右邊的 左邊的
03:22
all at the same time, bird's eye view,
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全都看到 就像在空中俯瞰
03:25
we will actually be able to see into those cars.
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我們能夠實際觀察其他車
03:28
We will be able to see the velocity of the car in front of us,
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我們可以知道前面車輛的速度
03:31
to see how fast that guy's going or stopping.
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其他司機開得多快或是否要停車
03:34
If that guy's going down to zero, I'll know.
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他要停車 我也會知道
03:38
And with computation and algorithms and predictive models,
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透過電腦計算、規則系統和預知模擬
03:42
we will be able to see the future.
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我們可以預知未來
03:46
You may think that's impossible.
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或許大家會覺得不可能
03:47
How can you predict the future? That's really hard.
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我們怎能預知未來 這太難了
03:50
Actually, no. With cars, it's not impossible.
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其實這不難 車輛可以做到
03:54
Cars are three-dimensional objects
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車是立體的
03:56
that have a fixed position and velocity.
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有固定的位置和速度
03:59
They travel down roads.
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在路上行駛
04:00
Often they travel on pre-published routes.
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通常在規劃好的路上行駛
04:03
It's really not that hard to make reasonable predictions
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要合理地預測 車子在短時間內
04:07
about where a car's going to be in the near future.
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會怎樣 並不困難
04:09
Even if, when you're in your car
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即使你駕駛時
04:11
and some motorcyclist comes -- bshoom! --
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遇到幾台機車 咻 !
04:13
85 miles an hour down, lane-splitting --
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以時速85英哩呼嘯而過 車子紛紛讓道
04:16
I know you've had this experience --
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相信大家都有這經驗吧
04:18
that guy didn't "just come out of nowhere."
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那人可不是憑空出現
04:21
That guy's been on the road probably for the last half hour.
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他說不定都已經在路上跑了半小時
04:25
(Laughter)
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[笑聲]
04:26
Right? I mean, somebody's seen him.
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是吧?我是說 一定有人看到他
04:29
Ten, 20, 30 miles back, someone's seen that guy,
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10哩前 20哩前 30哩前, 一定有人看到他
04:32
and as soon as one car sees that guy
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而只要有一部車看到他
04:34
and puts him on the map, he's on the map --
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把他放到地圖上 大家都會知道
04:37
position, velocity,
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他的位置和速度
04:39
good estimate he'll continue going 85 miles an hour.
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估計他會以每小時85英哩速度持續前進
04:41
You'll know, because your car will know, because
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你的車子預報 你便會知道這訊息
04:43
that other car will have whispered something in his ear,
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其他車也會對司機碎碎念
04:46
like, "By the way, five minutes,
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就像: 順便一提 再過5分鐘
04:48
motorcyclist, watch out."
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便會有機車 要小心
04:50
You can make reasonable predictions about how cars behave.
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你可以合理地預測車在路的情況
04:53
I mean, they're Newtonian objects.
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我是說 車子也遵從牛頓定律
04:54
That's very nice about them.
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還好是這樣
04:57
So how do we get there?
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那 我們要如何走到那一步?
05:00
We can start with something as simple
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我們可以開始分享我們車與車的位置
05:03
as sharing our position data between cars,
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從這件小事做起
05:05
just sharing GPS.
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就只是分享 GPS (全球定位系統)
05:07
If I have a GPS and a camera in my car,
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如果我的車子裝有 GPS 和鏡頭
05:10
I have a pretty precise idea of where I am
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我就能精確地知道我所在的位置
05:12
and how fast I'm going.
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以及我是以多快的速度前進
05:14
With computer vision, I can estimate where
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有電腦輔助 我還可以估算我旁邊哪裡有車
05:15
the cars around me are, sort of, and where they're going.
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以及他們要往哪裡去
05:19
And same with the other cars.
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其他車也可以知道
05:20
They can have a precise idea of where they are,
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他們可以知道自己身在何方
05:22
and sort of a vague idea of where the other cars are.
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也能大約了解其他車子的位置
05:24
What happens if two cars share that data,
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那麼如果兩部車子分享資訊, 會如何呢?
05:27
if they talk to each other?
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假設它們可以對話呢?
05:29
I can tell you exactly what happens.
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我可以告訴你會發生什麼事
05:32
Both models improve.
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兩部車都獲得行進間的改善
05:34
Everybody wins.
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是雙贏
05:36
Professor Bob Wang and his team
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Bob Wang 教授和他的團隊
05:39
have done computer simulations of what happens
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做了一個電腦模擬 看下列情況會產生什麼結果
05:42
when fuzzy estimates combine, even in light traffic,
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當集合一些粗估的資料 用在行車順暢的情況下,
05:45
when cars just share GPS data,
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讓車與車只是交換 GPS 資訊
05:48
and we've moved this research out of the computer simulation
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我們將這個研究帶離電腦模擬
05:50
and into robot test beds that have the actual sensors
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帶到裝有感應器的機器實驗上
05:53
that are in cars now on these robots:
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把原本放車子的裝置, 用到機器身上
05:56
stereo cameras, GPS,
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音響, 鏡頭, GPS
05:58
and the two-dimensional laser range finders
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還有平面雷射測距儀
06:00
that are common in backup systems.
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這些都是車子的標準配備
06:02
We also attach a discrete short-range communication radio,
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我們還裝上一台短距的無線電機台
06:07
and the robots talk to each other.
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讓機器可以相互溝通
06:09
When these robots come at each other,
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當兩部機器朝彼此前進
06:10
they track each other's position precisely,
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它們可以追蹤到彼此的精確位置
06:13
and they can avoid each other.
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因此可避免互撞
06:16
We're now adding more and more robots into the mix,
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我們現在在這個實驗中加入越來越多的機器
06:19
and we encountered some problems.
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然後我們遇到了一些狀況
06:21
One of the problems, when you get too much chatter,
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其一便是, 太吵了 當接收到太多瑣碎的言語
06:23
it's hard to process all the packets, so you have to prioritize,
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就很難去處理所有的資訊封包 這時就得選擇優先順序
06:27
and that's where the predictive model helps you.
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而預知模型系統 在這個時候就派上用場了
06:29
If your robot cars are all tracking the predicted trajectories,
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如果機器人車子 一直行駛在可預期的軌道上
06:33
you don't pay as much attention to those packets.
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就不用費心去解讀那些資訊封包
06:35
You prioritize the one guy
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首先被挑出的這個人
06:37
who seems to be going a little off course.
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往往就是有點偏移行進路線
06:38
That guy could be a problem.
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那麼這個人就有可能是個麻煩
06:41
And you can predict the new trajectory.
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然後你就可以再規劃一條新的軌道
06:44
So you don't only know that he's going off course, you know how.
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所以你不只知道他要偏離航道了 還知道他要怎麼偏
06:46
And you know which drivers you need to alert to get out of the way.
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也能知道遇到那個駕駛要提高警覺, 離遠一點
06:50
And we wanted to do -- how can we best alert everyone?
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我們希望 -- 我們要如何警告其他人?
06:53
How can these cars whisper, "You need to get out of the way?"
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這些車要怎麼小聲警告: "你得趕緊離開這裡"
06:56
Well, it depends on two things:
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嗯, 這得要兩個條件配合
06:58
one, the ability of the car,
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一, 車子的性能
07:00
and second the ability of the driver.
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二, 駕駛本身的技巧
07:03
If one guy has a really great car,
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就算這個人擁有一部很讚的車
07:04
but they're on their phone or, you know, doing something,
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但是他如果邊開邊做其他事 像講手機之類的
07:07
they're not probably in the best position
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他們可能就無法在緊急狀態中
07:09
to react in an emergency.
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做出最佳的反應
07:12
So we started a separate line of research
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因此我們又著手另一項實驗
07:14
doing driver state modeling.
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做有關駕駛者的狀態模型
07:16
And now, using a series of three cameras,
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我們使用三個一組的攝像機
07:19
we can detect if a driver is looking forward,
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來偵測這個駕駛人是看前面
07:21
looking away, looking down, on the phone,
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看別的地方, 看下面, 還是講手機
07:24
or having a cup of coffee.
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或喝咖啡
07:27
We can predict the accident
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我們可以預知事故
07:29
and we can predict who, which cars,
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我們可以知道是誰以及哪一部車子
07:33
are in the best position to move out of the way
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最好離開目前的道路
07:36
to calculate the safest route for everyone.
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並且幫每一個人規劃最安全的路徑
07:39
Fundamentally, these technologies exist today.
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最重要的是 這些科技在今天都已經有了
07:44
I think the biggest problem that we face
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我認為眼前最大的困難是
07:47
is our own willingness to share our data.
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大家是否願意做資訊分享
07:50
I think it's a very disconcerting notion,
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我想這樣的概念或許讓人有點不安
07:52
this idea that our cars will be watching us,
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因為我們的車子會監視著我們
07:55
talking about us to other cars,
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還跟別的車子打小報告
07:58
that we'll be going down the road in a sea of gossip.
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簡直就像航行在一片流言蜚語的汪洋中
08:02
But I believe it can be done in a way that protects our privacy,
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但是我相信, 我們還是可以 在保有隱私的情況下執行
08:05
just like right now, when I look at your car from the outside,
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好比現在, 如果我從外面看你的車
08:09
I don't really know about you.
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我不會知道你是何許人物
08:12
If I look at your license plate number,
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就算看著你的牌照號碼
08:13
I don't really know who you are.
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我也不會知道你是誰
08:15
I believe our cars can talk about us behind our backs.
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我相信我們的車子會在我們背後說長道短
08:19
(Laughter)
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[笑聲]
08:22
And I think it's going to be a great thing.
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但我認為那將會是件好事
08:25
I want you to consider for a moment
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花幾分鐘想想
08:27
if you really don't want the distracted teenager behind you
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你是不是真的不希望 那煩人的青少年在你背後
08:31
to know that you're braking,
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知道你要煞車
08:33
that you're coming to a dead stop.
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知道你要停下來
08:36
By sharing our data willingly,
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倘若各位願意分享
08:38
we can do what's best for everyone.
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我們可以幫每個人做到最好
08:41
So let your car gossip about you.
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所以 讓你的車去東家長西家短吧
08:44
It's going to make the roads a lot safer.
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這能讓道路使用更為安全
08:47
Thank you.
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謝謝各位
08:49
(Applause)
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[掌聲]
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