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Driving Innovation at the Edge: Chuck Gershman on AI, Silicon and Safer Autonomous Vehicles

33m 30s5,679 単語811 segmentsEnglish

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[Music]

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hi friends welcome again to another

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episode of beyond the clouds EDG to Edge

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transformation and transformation has to

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happen at every level I've been meeting

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some amazing entrepreneurs and Chuck uh

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I met him at a silicon Catalyst

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presentation for the last six months it

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was really amazing to hear the story of

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all autonomous Imaging for once AI

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doesn't start for artificial

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intelligence actually it does a little

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bit we we use AIML in our system the AI

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has a double on Tandra in this

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particular case on purpose that's

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perfect so uh Chuck tell us how did you

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end up being the Chuck of that we know

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now and how did you end up being in this

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company which is so

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amazing well I've been in the tech

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industry for three plus decades um I've

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had a very extensive career on the

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semiconductor uh side um I've also

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worked in iot and networking both on the

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digital and analog side of the business

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so a long long career at the chip level

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um at the subsystem level and even at

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the system level in some of the

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companies so seen a little bit of

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everything and uh tell us a little bit

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about all image and what do you guys do

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so AI uh we is ay that um that I

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co-founded with my partner Gan patii

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roughly 5 years ago at the time Gan had

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been working on Advanced uh imaging

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technology in the thermal domain he and

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I had worked on a project for the US Air

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Force that was quite sophisticated uh

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the beauty of that Air Force project was

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it was a proof of concept and the

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company that we worked for was able to

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retain all the intellectual property

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rights and that company's intellectual

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property rights eventually came to us to

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start start a new company so what got us

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motivated and what we do at Ali is we

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basically build a thermal night vision

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system uh and then we couple that with

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perception software specifically AIML

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software and the purpose of that is

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basically for safety so we build systems

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that go into automobiles trucks cars

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buses that are able to Independent of

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the driver uh visualize the entire scene

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and make uh real-time decisions on being

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able to avoid collisions accidents

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pedestrians animals Etc the system is

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designed in such a way that the driver

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of course could take action first but if

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the driver fails to respond the system

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can take over an ample time to make a

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safety decision uh and the goal of the

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company is simply to save

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lives and honestly when you told us

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about the data uh how many pedestrians

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get hurt especially when it's dark that

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was quite uh quite alarming uh can you

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tell us a little bit about that yeah so

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the statistics are not at all comforting

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in any way shape or form annually 1.4

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million people are killed in automobile

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accidents it is a very very significant

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um number however when you drill down on

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the numbers and 1.4 is a big number half

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of the people who are killed in car

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accidents weren't actually in the car

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they were pedestrians they were on

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bicycles they were on motorcycles they

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were on scooters they were walking down

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the street um that's one out of every

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two people killed and then if you drill

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down even further you'll find that 76%

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of those people actually were killed at

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night and this incident rate occurs not

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only for deaths but for just for any

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kind of incident so basically you know

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um automobile incidents at night is more

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than three qus of all incidents that

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occur especially when it comes to

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fatalities uh it's quite staggering can

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you combine this technology with many

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other technologies that are existing in

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the market

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and if so how does it work in

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tandem yeah so um in know we don't

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Envision um nor do we Advocate uh that

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the use of our particular sensor and

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software suite should be used

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independent of other sensors and

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software that are already existing in

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the vehicles or coming to market the

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basic premise is that we fill a gap in

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the overall sensor Suite with the

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uniqueness of what we do uh we build a

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system based on thermal imaging and then

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computer vision based on thermal imaging

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so there's still going to be visual

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cameras in the cars and they're still

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going to do what they do but they

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degrade at night just like humans

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degrade at night they degrade in foul

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weather so whether it's raining snowing

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sleep or if it's just Smoky or foggy um

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cameras will degrade thermal cameras

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their degradation in these conditions is

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a couple orders of magnitude less

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degradation we supplement these visual

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cameras we supplement Radars we

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supplement uh Imus we supplement all the

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other sensors to make a more robust

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overall system uh and again going back

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to the statistics the nighttime

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operation of these vehicles is

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definitely in question just like humans

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degrade at night in terms of their

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visualization so do the current sensor

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Suites that are in the cars and they

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just need to be better you said you've

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done some work with the Air Force have

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you been able to do some testing of your

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systems on the road and uh with humans

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and this

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point well um subsequent to our Air

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Force work which was done before we

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founded the company we have done work

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with the dod uh a as Al U mainly for

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what we call off-road so we've developed

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systems that are not on pavement the

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sensor systems obviously work fine but

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the software systems need to be slightly

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modified to work whether it's onroad or

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off-road so yes we do that um and we've

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already done that with the dod um but in

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terms of actual testing so the national

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highway traffic safety administration

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which is part of the Department of

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Transportation actually is is well aware

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of the statistics that I just

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articulated um and it has become quite

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an issue so we've seen that the US

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Congress under the infrastructure act

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has actually created line items to

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address um pedestrian safety uh as well

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as the European Union has now created

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regulatory respon so in the United

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States we now have regulations out there

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that are going to be mandatory by the

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end of the year that says You must be

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able to stop for a pedestrian at night

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at high speed um and that's going to be

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a minimum requirement to sell a vehicle

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in the United States by 2028 we see

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similar regulations in the in the

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European Union so these problems are not

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lost on governments now about a year ago

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Nitsa published a preliminary um set of

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recommendations which ultimately is

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going to become the final regulations so

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we took those

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specifications uh we went out to Detroit

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and rented time on a test track we took

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a we got a test vehicle we took our our

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full system we mounted it on the system

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we hired a test driver and we hired a

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third-party test company and we ran

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through the suite of nit a test now you

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said with real people we asked our

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interns whether they wanted to volunteer

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to run in front of the cars at 45 miles

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an hour we couldn't get anybody to agree

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so we Ed what's called electronic

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dummies um so these are mannequins that

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are on tracks they're heated um to give

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a thermal signature and you drive the

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vehicle down the track you hit a laser

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that triggers a certain speed and time

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and that triggers the dummy to run in

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front of the vehicle such the time it

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such that right when the car gets there

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so that was the test that we did we did

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this um 12 times times under different

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configurations we never struck the dummy

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now the same test that we were testing

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against has been tested against 21

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production vehicles and under the

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conditions that we tested against almost

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every one of those Vehicles ran over the

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dummy at one point in time or more the

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vehicles that are out there are not

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currently capable of passing these tests

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