字幕表 動画を再生する 英語字幕をプリント 90 percent of traffic accidents are caused by human error And the biggest risk factor in road traffic - is us. Forward collision accidents, lane departures. Our dream is to eliminate all those accidents totally – we call that “Vision Zero”. Technology from the holy city of Jerusalem, with a noble objective: Cars that won´t crash. This basically takes human error out of the equation. We should be able to save tens of thousands of lives with Vision Zero... Here at Mobileye, Amnon Shashua and his team are working on technologies that are transformative. It all begins with the understanding that just like a human can understand, by looking, what things are, where they are, and infer what they intend to do, the computer should be able to do the same. Making a computer see and interpret the world is game changing. Back in the late 90s when Mobileye was founded, we understood that such technology can make a life-saving impact. There was clear interest from the industry for Driving Assistance Systems - but the solutions were expensive and cumbersome. The industry thought that they needed stereo cameras they needed radars, they needed laser range finders. All those cumbersome systems. In fact, the human visual system relies on a diverse set of cues, all of them are monocular in nature, like perspective, motion, shading and context. Although it sounds unintuitive, doing this with a single camera, and mimicking the processes of the human visual system not only make it less expensive but also make it work better than other systems like stereo system relying mostly on geometric triangulation". Professor Amnon Shashua of the Hebrew University in Jerusalem returned from MIT where he completed his studies in computer vision and artificial intelligence with a vision to create a computerized “eye” for the sake of road safety. After founding the company with Ziv Aviram, he thought that the perfect person to lead the R&D of the nascent company would be his former student Dr. Gideon Stein. Shashua gathered other team members with diverse technical skills to solve the many different challenges. The first challenge is to detect the vehicles. You start by putting a bounding box on the vehicle in the image which is natural for a camera. Then comes the measurement. That´s the bigger problem because a camera is not a natural distance measurer. We had to develop smart algorithms to solve this problem. Prof Shashua's team at Mobileye have the objective to integrate a cheap and simple driver assistance system into any vehicle. So this is the basic system. So we have here the camera sensor and the lens, so this is the camera part. Here's the processor, our EyeQ processor. And this is the board which does everything which we need. The forward-looking camera behind the rear-view mirror sees what the driver sees. The software interprets the camera image. Artificial intelligence now has to draw the correct conclusions. But how can that be done without precise sensor data? Instead of using precise range measurements, the algorithms use the information from the camera's image to make a clever estimate. For instance, when calculating the distance. There we use perspective. We look at the bottom of the target whether it is a vehicle or a pedestrian, where the bottom is in the image. And its distance from the horizon gives us information about the distance to that vehicle. It's a bit more complicated than that, but that's the basic idea.” Mobileye has also found ways of making it work at low light, in rain, and on bumpy road surfaces. We were really formed in a garage but through a series of inventions we were ahead of everyone else. We filed patents, we improved the technology and today we are over 1.000 employees. To detect an impending collision in the camera image, Mobileye´s system uses a further trick: The second application is working out the time to collision. When are we going to hit the target? And there, we look at the expansion of the target in the image and that tells us something about when we're going to collide.” The objective: to warn the driver - in good time - of an impending crash. Today, Mobileye's “smart” driver assistance system is a world leader. In 2017 the company was bought for more than 13,5 billions Euros by the chip giant INTEL and Mobileye technology is now found in over 40 million vehicles. In this car, Mobileye installed a system with special image output - - to demonstrate everything the computer eye can see and what it calculates. During the car journey through Jerusalem, the screen shows the driver assistance system at work. So what we're doing is, we're detecting all the vehicles in the scene and for each vehicle we put the bounding box around the vehicle Every 27 milliseconds, algorithms calculate the distance and relative speed of the objects in the field of view. And the one vehicle which we care about most is the CIPV, the Current In-Path Vehicle, and it's marked with a hashed rectangle, and that is the vehicle from which we want to keep a safe distance. If it's an adaptive cruise control it'll monitor that distance, or just make sure we have a two-second headway from that vehicle. Meanwhile, a whole family of products is based on Mobileye's developments. If danger threatens, the systems warn the driver visually and acoustically - and can even be engineered to trigger an emergency braking manoeuvre all by themselves. The driver assistance system research also gave rise to another project: Mobileye is testing a fleet of driverless cars. Over the last seven years, the number of European patent applications in the driverless car sector has risen by 330 percent. Mobileye is at the forefront here as well. Driver assistance systems are still the project closest to the hearts of the inventors at Mobileye - because they save lives.
B1 中級 英 アムノン・シャシュアとモバイアイチーム - 交通安全を向上させる車両のビジョン (Amnon Shashua and the Mobileye Team - Vision for vehicles to improve road safety) 66 2 James に公開 2021 年 01 月 14 日 シェア シェア 保存 報告 動画の中の単語