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

48,314 views ・ 2013-04-25

TED


Dvaput kliknite na engleske titlove ispod za reprodukciju videozapisa.

00:00
Translator: Joseph Geni Reviewer: Morton Bast
0
0
7000
Prevoditelj: Martina Dolenčić Recezent: SIBELA KESAC
00:12
Let's face it:
1
12703
1914
Suočimo se
00:14
Driving is dangerous.
2
14617
2445
Vožnja je opasna.
00:17
It's one of the things that we don't like to think about,
3
17062
3098
To je jedna od stvari o kojima ne volimo razmišljati,
00:20
but the fact that religious icons and good luck charms
4
20160
3652
ali činjenica da se religijske ikone i simboli sreće
00:23
show up on dashboards around the world
5
23812
4790
pojavljuju na kontrolnim pločama po cijelome svijetu
00:28
betrays the fact that we know this to be true.
6
28602
4137
odaje činjenicu da znamo da je to istina.
00:32
Car accidents are the leading cause of death
7
32739
3594
Automobilske nesreće su glavni uzrok smrti
00:36
in people ages 16 to 19 in the United States --
8
36333
4170
kod ljudi starih 16 do 19 godina u Americi--
00:40
leading cause of death --
9
40503
2843
glavni uzrok smrti--
00:43
and 75 percent of these accidents have nothing to do
10
43346
3863
i 75% tih nesreća nema veze
00:47
with drugs or alcohol.
11
47209
2285
sa drogama i alkoholom.
00:49
So what happens?
12
49494
2261
Onda, što se događa?
00:51
No one can say for sure, but I remember my first accident.
13
51755
4219
Nitko ne može sa sigurnošću reći, ali ja se sjećam svoje prve nesreće.
00:55
I was a young driver out on the highway,
14
55974
3803
Bila sam mladi vozač na autocesti,
00:59
and the car in front of me, I saw the brake lights go on.
15
59777
2258
i automobil ispred mene, vidjela sam da se pale svjetla kočenja.
01:02
I'm like, "Okay, all right, this guy is slowing down,
16
62035
1800
Mislila sam, "Ok, sve u redu, on usporava,
01:03
I'll slow down too."
17
63835
1282
usporit ću i ja."
01:05
I step on the brake.
18
65117
1926
Pritisnula sam kočnicu.
01:07
But no, this guy isn't slowing down.
19
67043
2254
Ali ne, on ne usporava.
01:09
This guy is stopping, dead stop, dead stop on the highway.
20
69297
3178
On se zaustavlja, staje na autocesti.
01:12
It was just going 65 -- to zero?
21
72475
2540
Vozio je 100-- prema nuli?
01:15
I slammed on the brakes.
22
75015
1520
Nagazila sam na kočnicu.
01:16
I felt the ABS kick in, and the car is still going,
23
76535
3059
Osjetila sam ABS, a automobil se i dalje kreće,
01:19
and it's not going to stop, and I know it's not going to stop,
24
79594
2696
i neće se zaustaviti, znala sam da se neće zaustaviti,
01:22
and the air bag deploys, the car is totaled,
25
82290
2939
zračni jastuk se otvara, auto je totalka,
01:25
and fortunately, no one was hurt.
26
85229
3557
i na sreću, nitko nije nastradao.
01:28
But I had no idea that car was stopping,
27
88786
4211
Ali ja nisam imala pojma da se taj automobil zaustavljao,
01:32
and I think we can do a lot better than that.
28
92997
3645
i mislim da to možemo promijeniti.
01:36
I think we can transform the driving experience
29
96642
4145
Mislim da možemo promijeniti iskustvo vožnje
01:40
by letting our cars talk to each other.
30
100787
3879
tako da pustimo da automobili razgovaraju jedni s drugima.
01:44
I just want you to think a little bit
31
104666
1424
Samo želim da malo razmislite
01:46
about what the experience of driving is like now.
32
106090
2888
o iskustvu vožnje.
01:48
Get into your car. Close the door. You're in a glass bubble.
33
108978
4028
Uđite u svoj automobil. Zatvorite vrata. Vi ste u staklenom balonu.
01:53
You can't really directly sense the world around you.
34
113006
2916
Ne možete izravno osjetiti svijet oko vas.
01:55
You're in this extended body.
35
115922
2181
Vi ste u ovom proširenom tijelu.
01:58
You're tasked with navigating it down
36
118103
2163
Zaduženi ste da njime upravljate
02:00
partially-seen roadways,
37
120266
2056
djelomično vidljivim cestama,
02:02
in and amongst other metal giants, at super-human speeds.
38
122322
4424
u i među ostalim metalnim divovima, pri super ljudskim brzinama.
02:06
Okay? And all you have to guide you are your two eyes.
39
126746
4480
U redu? I sve što vas vodi su vaše oči.
02:11
Okay, so that's all you have,
40
131226
1762
U redu, to je sve što imate,
02:12
eyes that weren't really designed for this task,
41
132988
1735
oči koje zaista nisu stvorene za ovaj zadatak,
02:14
but then people ask you to do things like,
42
134723
3751
ali onda vas ljudi traže da radite stvari poput,
02:18
you want to make a lane change,
43
138474
1549
želite li se prestrojavati,
02:20
what's the first thing they ask you do?
44
140023
2321
koja je prva stvar koju vas traže da napravite?
02:22
Take your eyes off the road. That's right.
45
142344
3095
Skrenite pogled s ceste. Točno to.
02:25
Stop looking where you're going, turn,
46
145439
2096
Prestanite gledati kamo idete, okrenite se,
02:27
check your blind spot,
47
147535
2018
provjerite mrtvi kut,
02:29
and drive down the road without looking where you're going.
48
149553
3471
i vozite po cesti bez da gledate kamo idete.
02:33
You and everyone else. This is the safe way to drive.
49
153024
3135
Vi i svi ostali. To je siguran način vožnje.
02:36
Why do we do this? Because we have to,
50
156159
2241
Zašto to činimo? Zato što moramo,
02:38
we have to make a choice, do I look here or do I look here?
51
158400
2579
moramo odabrati, hoću li pogledati ovdje ili ondje?
02:40
What's more important?
52
160979
1521
Što je važnije?
02:42
And usually we do a fantastic job
53
162500
2711
I uglavnom odradimo fantastičan posao
02:45
picking and choosing what we attend to on the road.
54
165211
3769
i uspijemo opaziti sve bitno na cesti.
02:48
But occasionally we miss something.
55
168980
3650
Ali ponekad nešto propustimo.
02:52
Occasionally we sense something wrong or too late.
56
172630
4461
Ponekad opazimo nešto krivo ili prekasno.
02:57
In countless accidents, the driver says,
57
177091
1988
U bezbroj nesreća, vozači kažu,
02:59
"I didn't see it coming."
58
179079
2308
"Nisam vidio da dolazi."
03:01
And I believe that. I believe that.
59
181387
3281
I ja to vjerujem. Vjerujem.
03:04
We can only watch so much.
60
184668
2925
Ne možemo vidjeti sve.
03:07
But the technology exists now that can help us improve that.
61
187593
5144
Ali, s današnjom tehnologijom možemo to poboljšati.
03:12
In the future, with cars exchanging data with each other,
62
192737
4296
U budućnosti, sa izmjenom podataka među automobilima,
03:17
we will be able to see not just three cars ahead
63
197033
3928
bit ćemo u mogućnosti vidjeti, ne samo tri automobila sprijeda
03:20
and three cars behind, to the right and left,
64
200961
1594
i tri automobila straga, lijevo i desno,
03:22
all at the same time, bird's eye view,
65
202555
3166
sve u isto vrijeme, ptičja perspektiva,
03:25
we will actually be able to see into those cars.
66
205721
3128
već ćemo biti u mogućnosti vidjeti unutrašnjost tih automobila.
03:28
We will be able to see the velocity of the car in front of us,
67
208849
2371
Bit ćemo u mogućnosti vidjeti brzinu automobila ispred nas,
03:31
to see how fast that guy's going or stopping.
68
211220
3240
kako bi vidjeli kako brzo osoba vozi ili zastaje.
03:34
If that guy's going down to zero, I'll know.
69
214460
4510
Ako se ta osoba zaustavlja, znat ćemo.
03:38
And with computation and algorithms and predictive models,
70
218970
3859
I sa izračunima i algoritmima i predvidivim modelima,
03:42
we will be able to see the future.
71
222829
3273
bit ćemo u mogućnosti vidjeti budućnost.
03:46
You may think that's impossible.
72
226102
1556
Možda mislite da je to nemoguće.
03:47
How can you predict the future? That's really hard.
73
227658
2731
Kako možemo predvidjeti budućnost? To je zaista teško.
03:50
Actually, no. With cars, it's not impossible.
74
230389
3619
Zapravo, ne. Sa automobilima to nije nemoguće.
03:54
Cars are three-dimensional objects
75
234008
2732
Automobili su trodimenzionalni objekti
03:56
that have a fixed position and velocity.
76
236740
2332
koji imaju stalnu poziciju i brzinu.
03:59
They travel down roads.
77
239072
1631
Putuju cestama.
04:00
Often they travel on pre-published routes.
78
240703
2412
Često putuju na unaprijed objavljenim rutama.
04:03
It's really not that hard to make reasonable predictions
79
243115
3938
Zaista nije tako teško napraviti razumna predviđanja
04:07
about where a car's going to be in the near future.
80
247053
2864
o tome gdje će automobili biti u bližoj budućnosti.
04:09
Even if, when you're in your car
81
249917
2002
Čak i kada ste u automobilu
04:11
and some motorcyclist comes -- bshoom! --
82
251919
1994
i neki motociklist dolazi--bsoom!--
04:13
85 miles an hour down, lane-splitting --
83
253913
2296
135 kilometara na sat, po sredini ceste, između vozila,
04:16
I know you've had this experience --
84
256209
2547
Znam da ste imali ovakvo iskustvo--
04:18
that guy didn't "just come out of nowhere."
85
258756
2603
ta osoba nije došla "niotkuda."
04:21
That guy's been on the road probably for the last half hour.
86
261359
3643
Ta je osoba bila na cesti vjerojatno zadnjih pola sata.
04:25
(Laughter)
87
265002
1190
(Smijeh)
04:26
Right? I mean, somebody's seen him.
88
266192
3589
Zar ne? Mislim, netko ju je vidio.
04:29
Ten, 20, 30 miles back, someone's seen that guy,
89
269781
2768
10, 20, 30 kilometara otraga, netko je tu osobu vidio,
04:32
and as soon as one car sees that guy
90
272549
2384
i čim jedan automobil vidi tu osobu
04:34
and puts him on the map, he's on the map --
91
274933
2231
i stavi ga na kartu, on je na karti--
04:37
position, velocity,
92
277164
2176
pozicija, brzina,
04:39
good estimate he'll continue going 85 miles an hour.
93
279340
2321
vrlo je vjerojatno da će on nastaviti ići 135 km na sat.
04:41
You'll know, because your car will know, because
94
281661
2184
Vi ćete to znati, zato što će vaš automobil znati, jer
04:43
that other car will have whispered something in his ear,
95
283845
2275
će taj drugi automobil šapnuti nešto njemu na uho,
04:46
like, "By the way, five minutes,
96
286120
1923
poput, "Usput, pet minuta,
04:48
motorcyclist, watch out."
97
288043
2775
motociklist, pazi se."
04:50
You can make reasonable predictions about how cars behave.
98
290818
2703
Možete napraviti razumna predviđanja o tome kako se automobili ponašaju.
04:53
I mean, they're Newtonian objects.
99
293521
1365
Mislim, oni su Newtonovi objekti.
04:54
That's very nice about them.
100
294886
2909
To je ono lijepo kod njih.
04:57
So how do we get there?
101
297795
3034
Onda, kako stižemo tamo?
05:00
We can start with something as simple
102
300829
2266
Možemo započeti s nečim jednostavnim
05:03
as sharing our position data between cars,
103
303095
2870
poput razmjene podataka o našoj poziciji između automobila,
05:05
just sharing GPS.
104
305965
1892
samo dijeljenjem GPS-a.
05:07
If I have a GPS and a camera in my car,
105
307857
2444
Ako ja imam GPS i kameru u svom automobilu,
05:10
I have a pretty precise idea of where I am
106
310301
2231
Mogu prilično točno znati gdje se nalazim
05:12
and how fast I'm going.
107
312532
1732
i kako brzo se krećem.
05:14
With computer vision, I can estimate where
108
314264
1657
Pomoću računala, mogu otprilike procjeniti
05:15
the cars around me are, sort of, and where they're going.
109
315921
3537
gdje se nalaze automobile oko mene, i kamo idu.
05:19
And same with the other cars.
110
319458
970
I isto je sa ostalim autmobilima.
05:20
They can have a precise idea of where they are,
111
320428
1814
I oni mogu točno znati gdje se nalaze,
05:22
and sort of a vague idea of where the other cars are.
112
322242
2146
i otprilike znati gdje se nalaze ostali .
05:24
What happens if two cars share that data,
113
324388
3231
Što se događa ako dva automobila podijele te podatke,
05:27
if they talk to each other?
114
327619
1955
ako razgovaraju jedan s drugim?
05:29
I can tell you exactly what happens.
115
329574
2778
Mogu vam točno reći što se događa.
05:32
Both models improve.
116
332352
2339
Poboljšanje oba modela.
05:34
Everybody wins.
117
334691
2055
Svi su na dobitku.
05:36
Professor Bob Wang and his team
118
336746
2577
Profesor Bob Wang i njegov tim
05:39
have done computer simulations of what happens
119
339323
2738
napravili su računalnu simulaciju o tome što se događa
05:42
when fuzzy estimates combine, even in light traffic,
120
342061
3431
kada se kombiniraju nejasne procjene ,čak i sa semaforima
05:45
when cars just share GPS data,
121
345492
2624
kada automobili dijele GPS podatke,
05:48
and we've moved this research out of the computer simulation
122
348116
2513
i prenesli smo ovo istraživanje iz računalne simulacije
05:50
and into robot test beds that have the actual sensors
123
350629
3027
u probni robot koji ima stvarne senzore
05:53
that are in cars now on these robots:
124
353656
3133
koji su sada u automobilu na tim robotima:
05:56
stereo cameras, GPS,
125
356789
1838
kamera, GPS,
05:58
and the two-dimensional laser range finders
126
358627
1874
i dvodimenzionalni laserski daljinomjer
06:00
that are common in backup systems.
127
360501
2240
koji su uobičajeni u sigurnosnim sustavima.
06:02
We also attach a discrete short-range communication radio,
128
362741
4484
Također smo pridodali i diskretni komunikacijski radio kratkog dometa,
06:07
and the robots talk to each other.
129
367225
1909
i roboti pričaju jedni s drugima.
06:09
When these robots come at each other,
130
369134
1539
Kada ti roboti dođu jedan drugome,
06:10
they track each other's position precisely,
131
370673
2971
prate pozicije jedan drugome vrlo precizno,
06:13
and they can avoid each other.
132
373644
2737
i mogu izbjeći jedan drugoga.
06:16
We're now adding more and more robots into the mix,
133
376381
3226
Trenutno nadodajemo sve više i više robota u taj mix,
06:19
and we encountered some problems.
134
379607
1471
i naišli smo na neke probleme.
06:21
One of the problems, when you get too much chatter,
135
381078
2359
Jedan je problem, kada se previše brblja,
06:23
it's hard to process all the packets, so you have to prioritize,
136
383437
3728
teško je procesuirati sve pakete, pa morate odrediti prioritete,
06:27
and that's where the predictive model helps you.
137
387165
2357
i tu vam model predviđanja pomaže.
06:29
If your robot cars are all tracking the predicted trajectories,
138
389522
4372
Ako vaši roboti automobili svi prate predviđene putanje,
06:33
you don't pay as much attention to those packets.
139
393894
1767
ne obraćate toliko pozornosti na te pakete.
06:35
You prioritize the one guy
140
395661
1703
Prioritizirate jednu osobu
06:37
who seems to be going a little off course.
141
397364
1333
koja se čudno kreće.
06:38
That guy could be a problem.
142
398697
2526
Ta bi osoba mogla biti problem.
06:41
And you can predict the new trajectory.
143
401223
3002
I onda možete predvidjeti novu putanju.
06:44
So you don't only know that he's going off course, you know how.
144
404225
2763
Stoga ne samo da znate da se čudno kreće, već znate i kako.
06:46
And you know which drivers you need to alert to get out of the way.
145
406988
3725
I znate koje vozače morate upozoriti da se sklone s puta.
06:50
And we wanted to do -- how can we best alert everyone?
146
410713
2633
I želimo učiniti-- kako bi najbolje upozorili ostale?
06:53
How can these cars whisper, "You need to get out of the way?"
147
413346
3183
Kako mogu ti automobili šapnuti, "Moraš se skloniti s puta?"
06:56
Well, it depends on two things:
148
416529
1517
Pa, to ovisi o dvije stvari:
06:58
one, the ability of the car,
149
418046
2169
prva je sposobnost automobila,
07:00
and second the ability of the driver.
150
420215
3217
a druga sposobnost vozača.
07:03
If one guy has a really great car,
151
423432
1505
Ako neka osoba ima zaista super automobil,
07:04
but they're on their phone or, you know, doing something,
152
424937
2925
ali razgovara na mobitel, ili, znate već, nešto radi,
07:07
they're not probably in the best position
153
427862
1930
vjerojatno nisu u najboljoj poziciji
07:09
to react in an emergency.
154
429792
2970
da reagiraju na hitan slučaj.
07:12
So we started a separate line of research
155
432762
1665
Tako da smo počeli odvojenu liniju istraživanja
07:14
doing driver state modeling.
156
434427
2551
vezanu za stanje vozača.
07:16
And now, using a series of three cameras,
157
436978
2329
I sada, koristeći seriju od tri kamere,
07:19
we can detect if a driver is looking forward,
158
439307
2270
možemo detektirati ako vozač gleda naprijed,
07:21
looking away, looking down, on the phone,
159
441577
2860
gleda okolo, gleda dolje, ako je na telefonu,
07:24
or having a cup of coffee.
160
444437
3061
ili pije kavu.
07:27
We can predict the accident
161
447498
2070
Možemo predvidjeti nesreću
07:29
and we can predict who, which cars,
162
449568
3651
i možemo predvidjeti tko, koji automobili,
07:33
are in the best position to move out of the way
163
453219
3486
su u najboljoj poziciji da se maknu s puta
07:36
to calculate the safest route for everyone.
164
456705
3009
kako bi izračunali najsigurniju rutu za sve.
07:39
Fundamentally, these technologies exist today.
165
459714
4635
Fundamentalno, ova tehnologija danas postoji.
07:44
I think the biggest problem that we face
166
464349
2824
Mislim da je najveći problem s kojim se suočavamo
07:47
is our own willingness to share our data.
167
467173
3013
naša volja da podijelimo podatke.
07:50
I think it's a very disconcerting notion,
168
470186
2631
Mislim da je to vrlo neugodna zamisao,
07:52
this idea that our cars will be watching us,
169
472817
2386
ova ideja da će nas automobili gledati,
07:55
talking about us to other cars,
170
475203
3371
razgovarati o nama s ostalim automobilima,
07:58
that we'll be going down the road in a sea of gossip.
171
478574
3427
da ćemo ići cestom u moru tračeva.
08:02
But I believe it can be done in a way that protects our privacy,
172
482001
3897
Ali vjerujem da to može biti napravljeno na način da se zaštiti naša privatnost,
08:05
just like right now, when I look at your car from the outside,
173
485898
3741
kao što sada, kada gledam u vaš automobil izvana,
08:09
I don't really know about you.
174
489639
2363
zapravo ne znam ništa o vama.
08:12
If I look at your license plate number,
175
492002
1137
Ako pogledam broj vaše registarske ploče,
08:13
I don't really know who you are.
176
493139
1886
zapravo ne znam tko ste.
08:15
I believe our cars can talk about us behind our backs.
177
495025
4249
Vjerujem da naši automobili mogu razgovarati o nama iza naših leđa.
08:19
(Laughter)
178
499274
2975
(Smijeh)
08:22
And I think it's going to be a great thing.
179
502249
3185
I mislim da bi to bila odlična stvar.
08:25
I want you to consider for a moment
180
505434
1650
Želim da na trenutak razmotrite
08:27
if you really don't want the distracted teenager behind you
181
507084
4118
da li zaista ne želite da rastrojeni tinjedžera iza vas
08:31
to know that you're braking,
182
511202
2120
zna da vi kočite,
08:33
that you're coming to a dead stop.
183
513322
2924
da se zaustavljate.
08:36
By sharing our data willingly,
184
516246
2741
Šireći svoje podatke dobrovoljno,
08:38
we can do what's best for everyone.
185
518987
2812
možemo učini ono što je najbolje za svih.
08:41
So let your car gossip about you.
186
521799
3076
Stoga, dopustite da vas vaši automobili ogovaraju.
08:44
It's going to make the roads a lot safer.
187
524875
3038
To će učiniti ceste puno sigurnijima.
08:47
Thank you.
188
527913
1791
Hvala vam.
08:49
(Applause)
189
529704
4985
(Pljesak)
O ovoj web stranici

Ova stranica će vas upoznati s YouTube videozapisima koji su korisni za učenje engleskog jezika. Vidjet ćete lekcije engleskog koje vode vrhunski profesori iz cijelog svijeta. Dvaput kliknite na engleske titlove prikazane na svakoj video stranici da biste reproducirali video s tog mjesta. Titlovi se pomiču sinkronizirano s reprodukcijom videozapisa. Ako imate bilo kakvih komentara ili zahtjeva, obratite nam se putem ovog obrasca za kontakt.

https://forms.gle/WvT1wiN1qDtmnspy7