Civil Maps, Here and Nvidia are Pushing Self-Driving Cars Forward...

Mish Shedlock |

Via NVIDIA Corporation

Civil Maps, Here, Nvidia and other companies are working on a new kind of detailed cartography. Those new maps of the world will be for cars, not humans.



The weight of the automotive and tech industries is fully behind the move toward self-driving cars. Cars with “limited autonomy”—i.e., the ability to drive themselves under certain conditions (level 3) or within certain geofenced locations (level 4)—should be on our roads within the next five years.

But a completely autonomous vehicle—capable of driving anywhere, any time, with human input limited to telling it just a destination—remains a more distant goal. To make that happen, cars are going to need to know exactly where they are in the world with far greater precision than currently possible with technology like GPS. And that means new maps that are far more accurate than anything you could buy at the next gas station—not that a human would be able to read them anyway.

Fully aware of this need, car makers like BMW, Audi, Mercedes-Benz, and Ford have been voting with their wallets. They’re investing in companies like Here and Civil Maps that are building the platforms and gathering the data required. The end result will be a high-definition 3D map of our road networks—and everything within a few meters of them—that’s constantly updated by vehicles as they drive along.

Here started work building HD maps back in 2013, according to Sanjay Sood, the company’s VP for highly automated driving.

The first step is to create the initial map, which involves sensor-encrusted mapping vehicles that put Google’s Streetview cars to shame. Here uses a fleet of vehicles equipped with a roof-mounted sensor mast that packs 96 megapixels’ worth of cameras, a 32-beam Velodyne LIDAR scanner, and highly accurate Novatel GPS Inertial Measurement Units. These mapping vehicles drive around creating a 3D scan of the road and its surroundings that gets sent to Here’s cloud. From the cloud, that data is incorporated into a cm-accurate digital recreation of the real world.

“Starting last year, we’re essentially building the road network in order to have this map available for the first fleets of cars that are going to be leveraging this technology that are going to be showing up on the roads around 2020,” said Sood. “So we have to seed that ecosystem with a map.”

Maps will need to be constantly updated to reflect closures, road works, and other major obstacles.

Here has a couple of approaches to solving that problem. “We have hundreds of these mapping vehicles deployed around the globe,” Sood explains. “We have very in-depth relationships with many cities and regional authorities. So typically when there’s a large construction project happening, we know well before it even starts, and in many situations we can drive our vehicles there before the roads are open to the public.” That will allow Here to deploy updated maps (which typically arrive as 2km-by-2km tiles from Here’s cloud) to vehicles the day a certain road is opened or closed.

“How do you take all this heterogenous data and then make sense of it when you put it into a big data lake?” Sood told us. “That’s where a lot of the specialized skills that Here has come to the forefront.”

Not Just Graphics Cards

You may only know it for its GPUs, but Nvidia is becoming quite the player in this field, too, thanks to the company’s expertise with machine learning and deep neural networks. Those have plenty of applications in the self-driving world, and Nvidia is working with Here, as well as with TomTom, Baidu, and Zenrin, on mapping and cloud-to-car platforms. “HD maps are essential for self-driving cars,” said Jen-Hsun Huang, founder and chief executive officer of Nvidia. “Here’s adoption of our deep learning technology for their cloud-to-car mapping system will accelerate automakers’ ability to deploy self-driving vehicles.”
Nvidia’s technology—along with Intel’s—will also be required to slim down the bandwidth bills that will surely follow a crowdsourcing mapping fleet. “We’re developing a compute platform for the car, where the car itself does the change detection,” Sood said.

Problems Addressed

Every problem that readers throw at me is being addressed. I was not even aware of some of these companies until recently.

One reader commented something to the effect that cars will never be able to handle every conceivable road situations. That’s a ridiculously high standard, isn’t it?

I can conceive of lots of things. So what?

This is practical reality: Millions of long-haul truck jobs will vanish the moment level 4 is reached on highways. Every indication is level 4 for highways will be in place by 2020. Give it another year if you like, but competition ensures that outcome is soon assured.

Within a year of that event, millions of long-haul truck jobs will vanish. Taxi-related jobs will vanish as well, but likely at a slower pace.

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