这篇文章来自 wired.com。原始 url 是: https://www.wired.com/story/blackmore-doppler-lidar-self-driving-cars/
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随着每一个新 纽约客知道, 三济会痛苦地走得很慢。这是一个常见的观察, 现在它是一个可测量的, 多亏了 激光 雷达 激光扫描仪卡在货车的屋顶上, 目前正在指导我, 虽然繁忙时间交通在市中心 SF。
我以前做过大量的激光雷达探险, 但这是第一次, 不仅显示了行人, 骑自行车, 和其他车辆在我们周围, 但每一个速度。显示的不是数字, 而是颜色。从我们身上移开的东西都是红色的, 那些向我们移动的人都是蓝色的。他们走得越快, 色调就越暗。史蒂芬. 克劳奇指出了一个黄色 torsoed 的行人的深红四肢。"你看到的腿上, 他们是黑暗的," 他说-脚是一个人行走的最快的移动位。
克劳奇是一个创始人和 Blackmore 的首席技术官, 在蒙大拿州的启动, 使这种速度探测激光雷达系统。这是一个进步的潜力, 以帮助 自动驾驶车 看到, 理解, 并在拥挤的世界滑翔比以往任何时候都更容易。
速度, 你看, 是最简单的方法来确定什么是移动的地方, 相当重要的信息, 机器人试图确定什么值得注意。雷达可以测量速度-支撑自适应巡航控制和系统像特斯拉的自动驾驶仪-但它的分辨率是可怕的。基本上, 它可以告诉你, 50米那样的东西会在62.38 英里的时速向你驶来可能是一辆卡车, 可能是一群奶牛 从卡车上掉下来.
Lidar’s resolution is far better, but conventional systems can only provide indirect velocity data: You have to watch how far things move over time, comparing an image taken at one moment to the one taken milliseconds later. The problem there is that today’s systems, for all their laser points, don’t hit everything. Think of it like a game of Battleship—you need your laser to actually hit an object to know it’s there. That’s hard enough, especially at long distances. But you can only measure where something’s going, and how fast, if you manage to hit it again and again.
Of the dozens of companies hawking lidar systems for robo-cars, nearly all rely on this sort of deductive reasoning. They use what’s called a “time of flight” system, shooting out discrete pulses of light, measuring how long they take to bounce off the nearest object and come back. They then use the returns to build a 3-D map of what’s around the vehicle.
Blackmore uses what’s called a “frequency modulated continuous wave” setup, firing off one long, steady beam of light. (The light is in the 1,550 nanometer range, deep enough into the infrared spectrum to be invisible and harmless to human eyes.) This approach lets the company’s lidar sensor measure not just how long the light takes to come back, but its frequency when it does.
That’s where the Doppler effect comes in. Without dragging you back into high school physics, know that when that laser hits the dude on the scooter, its frequency changes based on his velocity: increasing if he’s coming toward you, decreasing if he’s going the same way. (In the visible light spectrum, blue light has the highest frequency, red the lowest, thus the color scheme.)
When that light returns to Blackmore’s lidar, the system measures its new frequency and calculates the speed and direction of whatever it hit. Then it couples it with the precise location of that thing, determined by timing how long the light takes to come back. Now, you don’t have to hope your laser finds that object again a moment later, so you calculate if and how it’s moving. A single shot gives you all the data you need.
A Doppler lidar like Blackmore’s does have one blind spot, however: It can’t detect the velocity of anything moving perpendicular to its laser beam. Which is a bit worrying considering the way pedestrians tend to cross the street.
Even so, this idea of simultaneous range and velocity is “super powerful,” says Kevin Peterson, a cofounder and software lead for Marble, a startup working on sidewalk delivery robots. Say a little dog is trotting down the road, and the lidar can pick out its general shape and size, but not the ears or legs—which would define it as an animal worth avoiding. With a conventional system, you have to keep detecting that small blob to know where it’s headed. Hit it with a Doppler lidar, Peterson says, and “I don’t know what it is, but I know I should avoid it. And I know where it’s going. That’s really valuable. Most of my time is spent trying to figure out how to track objects at long range.”
The idea of “Doppler lidar” isn’t new, of course. Researchers use it to measure wind velocity and turbulence. Cops use it to catch speeding motorists. But Blackmore managed to make it work on a moving car.
Which doesn’t mean the startup is going to win the lidar market, which, according to one report, will be worth close to $10 billion by 2032. Blackmore has a Doppler-reliant competitor in Aeva, a stealthy startup run by two former Apple engineers. And it still has to prove it can tackle the tricky issue of making a lidar that can survive a long lifetime on a vehicle that bounces through potholes and suffers through rain and snow and heat. Oh, and it also has to be cheap enough to sell to cost-conscious automakers, and scalable enough to put into mass production. It has to face down competition from the likes of Velodyne, which opened a lidar “megafactory” last year, and Luminar, which is ramping up to crank out thousands of its own far-seeing units.
But if Blackmore can handle all of that, it’s got a ticket into a market that’s just even red hot as the pedestrians it’ll see if it ever makes it to Manhattan.