Lvl5
Self-driving cars rely on high-definition maps to figure out exactly where they are, even if GPS fails.- Tesla collects data from its cars to build these maps for its own Autopilot and self-driving-car efforts.
- Two former Tesla engineers are taking a page out of Tesla's book by crowdsourcing data to build maps other automakers can use.
Andrew Kouri was working at Tesla when he noticed a big problem standing in the way of self-driving cars.
When it comes to autonomous driving capabilities, Tesla's cars are among the most sophisticated on the road. The electric carmaker's Autopilot system allows the vehicles to drive in heavy traffic and follow winding paths on highways.
But if the company wants its Model S and Model X cars to become truly autonomous and capable of handling any driving scenario, their current cameras and sensors alone aren't going to be enough.
Instead, they're going to need something else - like high-definition maps.
High-definition maps are like "sheet music" for self-driving cars, Kouri, now the founder of startup Lvl5, said in an interview. The cars can rely on the maps and their different landmarks to figure out where they are, even when GPS fails.
Companies have struggled to get maps with the level of detail necessary for self-driving cars. Not only do the maps have to be highly detailed, but they have to cover large swaths of land and be regularly updated as road conditions change.
"It came as a shock to me when I was at Tesla that Tesla couldn't find anyone to buy these maps from because no one really makes them yet," Kouri said.
Lvl5 aims to address that issue.
The company made its debut at this year's Y Combinator, an accelerator program for startups. With $2 million in seed funding, Lvl5 is crowdsourcing data to create high-definition maps of every route in the US. The startup aims to sell its maps directly to car companies.
The Tesla effect
Tesla
Lvl5 is taking a page right out of Tesla's book.In 2015, to address the mapping problem Kouri identified, Tesla CEO Elon Musk decided the company should build its own maps by collecting data from its Model S cars that were already on the road. Tesla has since ramped up those efforts by capturing short video clips from cameras installed on both its Model S and Model X vehicles.
That data is being used to build maps that help Tesla vehicles recognize things like street signs, traffic lights, and lane markings.
Kouri and his Lvl5 cofounder, Erik Reed, were engineers on Tesla's internal mapping team. The two are now using a similar model with their startup.
Lvl5 has teamed up with Uber and Lyft drivers to collect data for its own maps. Kouri designed an app called Payver, which is designed to snap a picture of the roads drivers are going down every meter that they travel. To use it, drivers simply have to download the app and position their phones so the devices' cameras can view the roadway in front of them.
"I went to [San Francisco International Airport], and there's an airport cell phone lot and another lot where all the Uber drivers wait," Kouri said. "I went in [to the Uber lot] and just started knocking on windows, handing out free phone mounts, and got a lot of people to sign up there."
The power of crowdsourcing
Since January, some 2,500 Uber and Lyft drivers have downloaded the app, Kouri said. The startup has already mapped 500,000 miles across the US.
Lvl5 is paying drivers 5 cents per mile when they take new routes. Otherwise it pays them 2 cents a mile.
Anyone can try out the app, but Uber and Lyft drivers have more of an incentive to use it, because they drive enough to actually see some significant money from it, Kouri said.
Lvl5's biggest advantage over automakers like Tesla that are trying to do the same thing is everyone can download and use its app, no matter what car they drive. That should give it wider coverage and allow it to collect more data.
Tesla, by contrast, can only collect data from its own vehicles, which limits the number of routes it can map.
"There are probably 50 [car manufacturers] and not all of them should have to have their own mapping division," Kouri said. "The goal is we will be the mapping provider for all of these companies."
But not every automaker is going it alone to create its own maps. BMW, Audi, and Mercedes, for example, are working together, pooling their data and handing it over to HERE, a digital map maker that the three German companies acquired for $3.1 billion in 2015.
Kouri said he considers HERE and rival navigation company TomTom to be Lvl5's biggest competitors. But because Lvl5 can update its maps more regularly through crowdsourcing, it has an advantage over them, he said.
"What we're doing is taking this crowdsourcing approach that Waze has and basically applying it to the self-driving-car problem," he said.
A drive for data
Waze, a real-time traffic app owned by Google, also collects data from people's smartphones to provide regular updates. The app, however, doesn't capture images of the road. Those images are crucial for building maps for self-driving cars.
Waymo, Google's self-driving sister company, uses vans equipped with lidar to map routes. But lidar, a sophisticated sensor akin to radar, is expensive. As a result, it's only installed on a small number of vehicles, and that limits how much mapping can be done in a single day.
"If you only have 20 of these vans, there's no way you're going to cover all the mileage in the world everyday," Kouri said.
Lvl5, however, doesn't intend to rely on Payver in the long term, Kouri said. Like Tesla and HERE, the startup wants to collect data captured by the cameras already installed on production vehicles.
Unlike its rivals though, Lvl5 doesn't plan to enter into any exclusive partnerships, Kouri said. Instead, it wants to continue to collect data from a wide array of car brands from all over the world.
It's too early to tell whether the startup's vision will pan out.
No automakers have signed up to use Lvl5's mapping technology yet, although one major automaker is pilot testing it. Kouri declined to name the automaker.
"If nobody has these global maps and nobody takes this crowdsourcing approach like we are, then you and I won't be able to have self-driving cars take us from our door to work," Kouri said.
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