Subtitles section Play video Print subtitles We all make poor life choices take these two guys for example They're the founders of a self driving car company called Zoox and they've decided it makes sense to try and compete against this Waymo the Google self driving car project, Cruise Automation, Daimler, Baidu, Uber, and Lyft But Zoox is different. its rivals are adding self driving technology to existing cars Meanwhile Zoox is making a new type of vehicle for the self driving age basically Zoox is making a robot and its early incarnation. Looks like the love child of the Matrix, Mad Max, and Transformers franchises This is Tim Kentley-Klay He hails from Australia and Down Under he was a well-known designer and ad guy One day he had an epiphany. A vision of the future full of robotic vehicles and came here to build them I sort of saw the future of how the whole system could work I said ok I need to find a brilliant computer scientist so that led me on a journey for six months actually where I ended up finding Jesse That brilliant computer scientist is Dr. Jesse Levinson A Stanford grad who was sought after by none other than Google itself I actually visited a Google X in 2013 to come and speak on my vision for autonomy In talking a fellow he there's one guy and he's really good and we can't get him that was my signal to go and get him a lot of your colleagues have run off to companies like Google or or Uber to retrofit their cars What drew you to this particular task and this approach I've been working on some driving cars since 2005 and it's pretty clear even back then that there's going to be one of the more transformative technologies for society It wasn't enough to just solve the technology You need a product and you need a business that makes sense And I hadn't seen that in any other company until I met Tim and he shared his high level vision For what Zoox could be And that vision is a system of completely autonomous robotic vehicles that can be summoned just like a Lyft, or dare I saw it, an Uber We have a very clear vision at Zoox which is that AI and mobility will take us out of the age of the automobile and into the next mobility age which for us is robotics autonomous transportation Tim and Jesse take me to the Alameda Naval Air Station where I'm about to get a test drive and see how a Zooks robot handles these are very unique vehicles. They're designed in a way that would only make sense if they're going to be fully autonomous The power trains are designed for full autonomy they are fully redundant and they have joule high voltage batteries they have joule low voltage architectures you can see that rigged with computer sensors. They can drive without any human intervention This is VH4. This is VH5 You want to go for a ride?. Yeah I do. All right. Jump in Zoox has placed cones on the tarmac. The robot is going to drive out and try to dodge them And I get to do the whole test sitting backwards because Tim thought it would be funny time to meet my robot maker and with one swift keystroke I give complete control of my life over to an ai That really doesn't get old. It's like being at a ride at Disney. These AI robots crank through the course at forty five miles per hour. And the VH5 is set to rip through it at a delightful seventy five miles per hour We can choose all wheel steering, two wheel steering, crab steering, dual Motors and then we have direction I like the crab Steering. Zoox got its start here in this abandoned firehouse back in 2015 with only six employees They've since raised an astonishing eight hundred million dollars and have expanded their operations into a one stop robot making shop With the help of 400 employees. Zoox now on their way to turning these prototypes into full fledged vehicles by 2020 For the moment though Zoox does most of its software testing in these Modified versions of Toyota Highlander's which have the decided advantage of being street legal. We're actually going to get you to drive autonomously from this facility to our new headquarters in Foster City And then Jesse is going to jump in and you can travel to downtown San Francisco We don't know any company in the world that is driving that multi-dimensional degree of difficulty from urban to freeway to dense downtown So that's a that's a bicycle? That was a cyclist yeah and that's the car behind us Is something like the speed limit, does that get taken by the cameras seeing the signs or is that something that has to get entered in as you map the world? If there's a sign that's been vandalized or it's missing, or you know, it's got growth on it The vehicle wouldn't know what the speed limit is and that could cause an incident right or a fine So speed limits are really well understood on the road networks. So we put that in as a primer on the map Ok So coming up right here we have to do a left turn yield So you got to see this other car Yes so were we would be concerned about this car that's coming towards us from a prediction level So we just want to make sure that they do the right thing And now we're yielding so if you look on this screen see this yellow here That means we're yielding for that vehicle Ok And now we're off We're about to drive onto the freeway so this will be interesting you can see there's quite a bit of traffic on our left and the vehicles indicating at the moment it's going to break a little bit harder because we've got this vehicle right on our 6 and we're running out of runway. And now we merge in. So that would have been a hard situation even for a human driver. We needed to merge and that person on the left was not letting us in We tried to go in front. They stayed with us and then we had to break, let them go past, and then we pulled in. That was, that was all autonomous and you could see how smooth that was Good robot So one of the hardest things to do with autonomous driving is actually prediction because you not only need to understand whats the state of the world is, you have to say well what's the state of the world in the near future If I do this what will that person do. And so that creates very quickly a large search tree and if the vehicle is going to drive with good performance you need to be able to predict well what the state of the world is in the near future Here's our new headquarters 20 minutes suburban driving, freeways merging, 100 percent autonomous That was incredible That was amazing Alright guy, let's go two for two. No pressure Whats' like in each box it looks like there's like a Y an L Yeah there's a V an R and an L. So V means vision, R means radar, and L means LIDAR So we use cameras. We use radar and we use LIDAR Cameras are really good at seeing what things are Radar is really good at seeing where things are in terms of how far away they are And then LIDAR is really good at telling you where things are in 3-D at pretty high resolution and pretty high accuracy And so what we do is we fuse those three sensors together in real time to form one coherent view of the world which is actually what you're looking at on the screen Definitely crowded I mean that must make it harder Oh yeah it's a lot to keep track of We have made it autonomously to San Francisco As far as the public knows Zoox along with Waymo, and GM cruise, are the only companies capable of doing this kind of drive and this is the first time they've ever shown the cars in action to the public Is it madness to take on many of the world's leading automotive and tech companies at the same time? Yes, Of course it is But I say go fourth Tim and Jessie. We all await our lux robotic ride share of the future
B1 US autonomous driving robot jesse vehicle drive The $800M Robo Taxi That Could Beat Uber 57 1 Samuel posted on 2018/09/21 More Share Save Report Video vocabulary