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

48,736 views ・ 2013-04-25

TED


Please double-click on the English subtitles below to play the video.

00:00
Translator: Joseph Geni Reviewer: Morton Bast
0
0
7000
Prevodilac: Mile Živković Lektor: Dejan Vicai
00:12
Let's face it:
1
12703
1914
Suočimo se s tim:
00:14
Driving is dangerous.
2
14617
2445
vožnja automobila 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 da mislimo,
00:20
but the fact that religious icons and good luck charms
4
20160
3652
ali činjenica da se religiozne ikone i amajlije
00:23
show up on dashboards around the world
5
23812
4790
pojavljuju na instrument-tablama širom sveta
00:28
betrays the fact that we know this to be true.
6
28602
4137
odaje činjenicu da znamo da je ovo istina.
00:32
Car accidents are the leading cause of death
7
32739
3594
Saobraćajne nesreće su vodeći uzrok smrti
00:36
in people ages 16 to 19 in the United States --
8
36333
4170
kod ljudi između 16 i 19 godina u SAD -
00:40
leading cause of death --
9
40503
2843
vodeći uzrok smrti -
00:43
and 75 percent of these accidents have nothing to do
10
43346
3863
i 75% ovih nesreća nema nikakve veze
00:47
with drugs or alcohol.
11
47209
2285
sa drogama ili alkoholom.
00:49
So what happens?
12
49494
2261
Pa šta se dešava?
00:51
No one can say for sure, but I remember my first accident.
13
51755
4219
Niko ne zna tačno, ali sećam se svoje prve nesreće.
00:55
I was a young driver out on the highway,
14
55974
3803
Bila sam mladi vozač na autoputu,
00:59
and the car in front of me, I saw the brake lights go on.
15
59777
2258
i videla sam da su se upalila stop svetla vozila ispred mene.
01:02
I'm like, "Okay, all right, this guy is slowing down,
16
62035
1800
Rekla sam: "Okej, sve je u redu, ovaj tip usporava,
01:03
I'll slow down too."
17
63835
1282
i ja ću da usporim."
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, ovaj tip ne usporava.
01:09
This guy is stopping, dead stop, dead stop on the highway.
20
69297
3178
On staje, u mestu, na autoputu.
01:12
It was just going 65 -- to zero?
21
72475
2540
Išao je 110 na sat - do nule?
01:15
I slammed on the brakes.
22
75015
1520
Nagazila sam kočnicu.
01:16
I felt the ABS kick in, and the car is still going,
23
76535
3059
Osetila sam kako se aktivira ABS, i auto još uvek ide,
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 i znam da se neće zaustaviti,
01:22
and the air bag deploys, the car is totaled,
25
82290
2939
i aktivira se vazdušni jastuk, auto je uništen,
01:25
and fortunately, no one was hurt.
26
85229
3557
i na sreću, niko nije povređen.
01:28
But I had no idea that car was stopping,
27
88786
4211
Ali nisam imala pojma da će taj auto stati,
01:32
and I think we can do a lot better than that.
28
92997
3645
i mislim da to možemo da radimo puno bolje.
01:36
I think we can transform the driving experience
29
96642
4145
Mislim da možemo preobratiti doživljaj vožnje
01:40
by letting our cars talk to each other.
30
100787
3879
tako što ćemo automobilima dozvoliti da međusobno pričaju.
01:44
I just want you to think a little bit
31
104666
1424
Želim da na trenutak razmislite
01:46
about what the experience of driving is like now.
32
106090
2888
o tome kakav je sada doživljaj vožnje.
01:48
Get into your car. Close the door. You're in a glass bubble.
33
108978
4028
Uđete u automobil. Zatvorite vrata. U staklenom ste zvonu.
01:53
You can't really directly sense the world around you.
34
113006
2916
Ne možete direktno osetiti svet oko vas.
01:55
You're in this extended body.
35
115922
2181
U produženom ste telu.
01:58
You're tasked with navigating it down
36
118103
2163
Imate zadatak da njime idete
02:00
partially-seen roadways,
37
120266
2056
putevima koje vidite delimično,
02:02
in and amongst other metal giants, at super-human speeds.
38
122322
4424
među drugim metalnim divovima, pri nadljudskim brzinama.
02:06
Okay? And all you have to guide you are your two eyes.
39
126746
4480
U redu? Sve što vas vodi su vaša dva oka.
02:11
Okay, so that's all you have,
40
131226
1762
To je sve što imate,
02:12
eyes that weren't really designed for this task,
41
132988
1735
oči koje nisu baš stvorene za ovaj zadatak,
02:14
but then people ask you to do things like,
42
134723
3751
ali vas onda ljudi pitaju da radite stvari poput
02:18
you want to make a lane change,
43
138474
1549
menjanja traka na putu,
02:20
what's the first thing they ask you do?
44
140023
2321
šta je prva stvar koju traže od vas?
02:22
Take your eyes off the road. That's right.
45
142344
3095
Da sklonite oči s puta. Tako je.
02:25
Stop looking where you're going, turn,
46
145439
2096
Prestanete da gledate kuda idete, skrenete,
02:27
check your blind spot,
47
147535
2018
proverite mrtvi ugao,
02:29
and drive down the road without looking where you're going.
48
149553
3471
i vozite putem bez gledanja kuda idete.
02:33
You and everyone else. This is the safe way to drive.
49
153024
3135
Vi i svi ostali. Ovo je bezbedan način vožnje.
02:36
Why do we do this? Because we have to,
50
156159
2241
Zašto radimo ovo? Jer moramo,
02:38
we have to make a choice, do I look here or do I look here?
51
158400
2579
moramo da odaberemo, da li da gledam ovde ili onde?
02:40
What's more important?
52
160979
1521
Šta je bitnije?
02:42
And usually we do a fantastic job
53
162500
2711
Obično fantastično odaberemo
02:45
picking and choosing what we attend to on the road.
54
165211
3769
to čemu ćemo posvetiti pažnju na putu.
02:48
But occasionally we miss something.
55
168980
3650
Ali povremeno nam nešto izmakne.
02:52
Occasionally we sense something wrong or too late.
56
172630
4461
Povremeno nešto opazimo na pogrešan način ili prekasno.
02:57
In countless accidents, the driver says,
57
177091
1988
U velikom broju nesreća, vozači kažu:
02:59
"I didn't see it coming."
58
179079
2308
"Nisam video da dolazi."
03:01
And I believe that. I believe that.
59
181387
3281
I ja verujem u to. Verujem u to.
03:04
We can only watch so much.
60
184668
2925
Možemo videti samo određeni deo toga.
03:07
But the technology exists now that can help us improve that.
61
187593
5144
Ali sada postoji tehnologija koja može da nam pomogne da to unapredimo.
03:12
In the future, with cars exchanging data with each other,
62
192737
4296
U budućnosti će automobili međusobno razmenjivati informacije,
03:17
we will be able to see not just three cars ahead
63
197033
3928
i moći ćemo da vidimo ne samo ispred tri automobila
03:20
and three cars behind, to the right and left,
64
200961
1594
i iza tri automobila, levo i desno,
03:22
all at the same time, bird's eye view,
65
202555
3166
i sve u isto vreme, ptičju perspektivu,
03:25
we will actually be able to see into those cars.
66
205721
3128
moći ćemo da vidimo i unutar tih automobila.
03:28
We will be able to see the velocity of the car in front of us,
67
208849
2371
Moći ćemo da vidimo brzinu automobila ispred nas,
03:31
to see how fast that guy's going or stopping.
68
211220
3240
da vidimo koliko brzo ide ili se zaustavlja.
03:34
If that guy's going down to zero, I'll know.
69
214460
4510
Ako će skroz stati, ja ću to da znam.
03:38
And with computation and algorithms and predictive models,
70
218970
3859
S proračunima, algoritmima i modelima predviđanja
03:42
we will be able to see the future.
71
222829
3273
moći ćemo da vidimo 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 predvideti budućnost? To je jako teško.
03:50
Actually, no. With cars, it's not impossible.
74
230389
3619
Zapravo nije. S automobilima, 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
s fiksiranom pozicijom i brzinom.
03:59
They travel down roads.
77
239072
1631
Kreću se putevima.
04:00
Often they travel on pre-published routes.
78
240703
2412
Često unapred poznatim trasama.
04:03
It's really not that hard to make reasonable predictions
79
243115
3938
Zaista nije teško napraviti razumna predviđanja
04:07
about where a car's going to be in the near future.
80
247053
2864
o tome gde će automobil biti u bliskoj budućnosti.
04:09
Even if, when you're in your car
81
249917
2002
Čak i ako ste u svojim kolima
04:11
and some motorcyclist comes -- bshoom! --
82
251919
1994
i neki motociklista prođe - vrum! -
04:13
85 miles an hour down, lane-splitting --
83
253913
2296
135 kilometara na sat, menjajući trake -
04:16
I know you've had this experience --
84
256209
2547
znam da ste iskusili ovo -
04:18
that guy didn't "just come out of nowhere."
85
258756
2603
taj tip se nije samo "pojavio niotkuda."
04:21
That guy's been on the road probably for the last half hour.
86
261359
3643
Taj tip je verovatno bio na putu poslednjih pola sata.
04:25
(Laughter)
87
265002
1190
(Smeh)
04:26
Right? I mean, somebody's seen him.
88
266192
3589
Zar ne? Mislim, neko ga je video.
04:29
Ten, 20, 30 miles back, someone's seen that guy,
89
269781
2768
Pre nekih 30 - 50 kilometara, neko ga je video,
04:32
and as soon as one car sees that guy
90
272549
2384
i čim ga vidi jedan automobil
04:34
and puts him on the map, he's on the map --
91
274933
2231
i stavi ga na mapu, on je na mapi -
04:37
position, velocity,
92
277164
2176
pozicija, brzina,
04:39
good estimate he'll continue going 85 miles an hour.
93
279340
2321
dobra procena da će nastaviti da ide 135km/h.
04:41
You'll know, because your car will know, because
94
281661
2184
Vi ćete to znati, jer će vaš automobil to znati,
04:43
that other car will have whispered something in his ear,
95
283845
2275
jer će mu to šapnuti neki drugi automobil:
04:46
like, "By the way, five minutes,
96
286120
1923
"E da, za pet minuta,
04:48
motorcyclist, watch out."
97
288043
2775
motociklista, pazi se."
04:50
You can make reasonable predictions about how cars behave.
98
290818
2703
Možete imati razumna predviđanja o tome kako će se ponašati automobili.
04:53
I mean, they're Newtonian objects.
99
293521
1365
To su Njutnovski objekti.
04:54
That's very nice about them.
100
294886
2909
To je lepa stvar u vezi sa njima.
04:57
So how do we get there?
101
297795
3034
Kako doći do toga?
05:00
We can start with something as simple
102
300829
2266
Možemo početi s nečim tako jednostavnim
05:03
as sharing our position data between cars,
103
303095
2870
poput razmenjivanja podataka o poziciji među automobilima,
05:05
just sharing GPS.
104
305965
1892
samo razmenom GPS-a.
05:07
If I have a GPS and a camera in my car,
105
307857
2444
Ako u kolima imam GPS i kameru,
05:10
I have a pretty precise idea of where I am
106
310301
2231
imam prilično dobar osećaj toga gde sam
05:12
and how fast I'm going.
107
312532
1732
i koliko brzo se krećem.
05:14
With computer vision, I can estimate where
108
314264
1657
Sa kompjuterskim vidom, mogu da procenim
05:15
the cars around me are, sort of, and where they're going.
109
315921
3537
gde se nalaze kola oko mene, na neki način i kuda idu.
05:19
And same with the other cars.
110
319458
970
Isto je sa drugim automobilima.
05:20
They can have a precise idea of where they are,
111
320428
1814
Mogu da imaju precizan osećaj o tome gde su,
05:22
and sort of a vague idea of where the other cars are.
112
322242
2146
i nejasan osećaj o tome gde su drugi automobili.
05:24
What happens if two cars share that data,
113
324388
3231
Šta se desi ako dva automobila dele 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
Reći ću vam tačno šta se dešava.
05:32
Both models improve.
116
332352
2339
Oba modela se poboljšaju.
05:34
Everybody wins.
117
334691
2055
Svi su na dobitku.
05:36
Professor Bob Wang and his team
118
336746
2577
Profesor Bob Veng i njegov tim
05:39
have done computer simulations of what happens
119
339323
2738
su uradili kompjuterske simulacije toga šta se dešava
05:42
when fuzzy estimates combine, even in light traffic,
120
342061
3431
kada se nejasne procene kombinuju, čak i u lakšem saobraćaju
05:45
when cars just share GPS data,
121
345492
2624
kada automobili samo dele GPS podatke,
05:48
and we've moved this research out of the computer simulation
122
348116
2513
i ovo istraživanje smo prebacili iz kompjuterske simulacije
05:50
and into robot test beds that have the actual sensors
123
350629
3027
u robote za testiranje koji imaju prave senzore
05:53
that are in cars now on these robots:
124
353656
3133
koji su sada u automobilima na ovim robotima:
05:56
stereo cameras, GPS,
125
356789
1838
stereo kamere, GPS,
05:58
and the two-dimensional laser range finders
126
358627
1874
i dvodimenzionalne laserske detektore dometa
06:00
that are common in backup systems.
127
360501
2240
koji su česti u sistemima za podršku.
06:02
We also attach a discrete short-range communication radio,
128
362741
4484
Takođe stavljamo diskretni kratkodometni radio za komunikaciju
06:07
and the robots talk to each other.
129
367225
1909
i roboti međusobno pričaju.
06:09
When these robots come at each other,
130
369134
1539
Kada se ovi roboti susretnu,
06:10
they track each other's position precisely,
131
370673
2971
oni jedan drugom precizno prate poziciju
06:13
and they can avoid each other.
132
373644
2737
i mogu da se mimoiđu.
06:16
We're now adding more and more robots into the mix,
133
376381
3226
Sada u priču dodajemo sve više i više robota
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 od problema je, kada dođe do previše čavrljanja,
06:23
it's hard to process all the packets, so you have to prioritize,
136
383437
3728
teško je obraditi sve podatke, tako da morate da ih poređate po prioritetu
06:27
and that's where the predictive model helps you.
137
387165
2357
i tu vam pomaže model predviđanja.
06:29
If your robot cars are all tracking the predicted trajectories,
138
389522
4372
Ako svi vaši robotski automobili prate predviđene putanje
06:33
you don't pay as much attention to those packets.
139
393894
1767
na te podatke ne obraćate toliko pažnje.
06:35
You prioritize the one guy
140
395661
1703
Prioritet date onom tipu
06:37
who seems to be going a little off course.
141
397364
1333
koji izgleda kao da ide malo van putanje.
06:38
That guy could be a problem.
142
398697
2526
Taj tip bi mogao da bude problematičan.
06:41
And you can predict the new trajectory.
143
401223
3002
I možete predvideti novu putanju.
06:44
So you don't only know that he's going off course, you know how.
144
404225
2763
Sada nećete znati samo da ide van putanje, nego i kako to radi.
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 obavestiti da se sklone s puta.
06:50
And we wanted to do -- how can we best alert everyone?
146
410713
2633
I hteli smo da uradimo - kako najbolje obavestiti svakoga?
06:53
How can these cars whisper, "You need to get out of the way?"
147
413346
3183
Kako da ovi automobili šapnu: "Moraš da se skloniš s puta?"
06:56
Well, it depends on two things:
148
416529
1517
To zavisi od dve stvari:
06:58
one, the ability of the car,
149
418046
2169
pod jedan, mogućnosti automobila
07:00
and second the ability of the driver.
150
420215
3217
i pod dva, mogućnosti vozača.
07:03
If one guy has a really great car,
151
423432
1505
Ako jedan čovek ima stvarno odličan automobil,
07:04
but they're on their phone or, you know, doing something,
152
424937
2925
ali priča na telefon ili već radi nešto,
07:07
they're not probably in the best position
153
427862
1930
verovatno nije u najboljoj poziciji
07:09
to react in an emergency.
154
429792
2970
da reaguje u hitnom slučaju.
07:12
So we started a separate line of research
155
432762
1665
Počeli smo poseban deo istraživanja
07:14
doing driver state modeling.
156
434427
2551
gde smo modelirali stanje vozača.
07:16
And now, using a series of three cameras,
157
436978
2329
Koristeći komplet od tri kamere
07:19
we can detect if a driver is looking forward,
158
439307
2270
sada možemo otkriti da li vozač gleda napred,
07:21
looking away, looking down, on the phone,
159
441577
2860
u stranu, dole, da li telefonira
07:24
or having a cup of coffee.
160
444437
3061
ili pije kafu.
07:27
We can predict the accident
161
447498
2070
Možemo predvideti nesreću
07:29
and we can predict who, which cars,
162
449568
3651
i možemo predvideti ko i koji automobili
07:33
are in the best position to move out of the way
163
453219
3486
su u najboljoj poziciji da se sklone
07:36
to calculate the safest route for everyone.
164
456705
3009
i izračunaju najbezbedniju putanju za sve.
07:39
Fundamentally, these technologies exist today.
165
459714
4635
U osnovi, ove tehnologije danas postoje.
07:44
I think the biggest problem that we face
166
464349
2824
Mislim da je najveći problem sa kojim se suočavamo
07:47
is our own willingness to share our data.
167
467173
3013
naša volja da podelimo svoje podatke.
07:50
I think it's a very disconcerting notion,
168
470186
2631
Mislim da je to veoma uznemiravajuća zamisao,
07:52
this idea that our cars will be watching us,
169
472817
2386
da će nas posmatrati naši automobili,
07:55
talking about us to other cars,
170
475203
3371
o nama pričati sa drugim automobilima,
07:58
that we'll be going down the road in a sea of gossip.
171
478574
3427
da ćemo putem ići u moru tračeva.
08:02
But I believe it can be done in a way that protects our privacy,
172
482001
3897
Ali verujem da se to može uraditi na način koji štiti našu privatnost,
08:05
just like right now, when I look at your car from the outside,
173
485898
3741
kao sada, kada pogledam vaš automobil spolja,
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 vaših tablica,
08:13
I don't really know who you are.
176
493139
1886
zaista ne znam ko ste vi.
08:15
I believe our cars can talk about us behind our backs.
177
495025
4249
Mislim da naši automobili mogu da pričaju o nama iza naših leđa.
08:19
(Laughter)
178
499274
2975
(Smeh)
08:22
And I think it's going to be a great thing.
179
502249
3185
Mislim da će to biti sjajna stvar.
08:25
I want you to consider for a moment
180
505434
1650
Želim da za trenutak razmotrite
08:27
if you really don't want the distracted teenager behind you
181
507084
4118
da li zaista želite da rastrojeni tinejdžer iza vas
08:31
to know that you're braking,
182
511202
2120
ne zna da kočite,
08:33
that you're coming to a dead stop.
183
513322
2924
da stajete u mestu.
08:36
By sharing our data willingly,
184
516246
2741
Ako voljno delimo svoje podatke,
08:38
we can do what's best for everyone.
185
518987
2812
možemo uraditi ono što je najbolje za sve.
08:41
So let your car gossip about you.
186
521799
3076
Pustite vaš automobil da trača o vama.
08:44
It's going to make the roads a lot safer.
187
524875
3038
To će puteve učiniti puno bezbednijim.
08:47
Thank you.
188
527913
1791
Hvala vam.
08:49
(Applause)
189
529704
4985
(Aplauz)
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7