2 ex-Tesla engineers are using an old trick from Elon Musk to build their new startup
- Self-driving cars rely on high-definition maps to know exactly where they are even if GPS fails.
- Tesla collects data from its cars to build these maps for its 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-car maker’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, the vehicle’s cameras and sensors alone won’t be enough.
Instead, they will need something else — like high-definition maps.
High-definition maps are like “sheet music” for self-driving cars, Kouri, now a cofounder of the 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 also 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 with the goal of creating high-definition maps of every route in the US. The startup aims to sell its maps directly to car companies.
The Tesla effect
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 maps. Kouri designed an app, called Payver, that is designed to snap a picture of the road after every meter a driver travels. To use it, drivers simply have to download the app and position their phone so the device’s camera can view the road in front of them.
To help recruit Uber drivers, Kouri said, he went window-to-window at a San Francisco International Airport parking lot where Uber drivers wait to pick up passengers.
“I went in and just started knocking on windows, handing out free phone mounts, and got a lot of people to sign up there,” he said.
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 $0.05 a mile when they take new routes. Otherwise it pays them $0.02 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 that its app can be used in any car. That should give it wider coverage and allow it to collect more data.
Tesla, by contrast, can collect data only from its own vehicles, which limits the number of routes it can map.
Not all car manufacturers, Kouri said, “should have to have their own mapping division.” He continued: “The goal is we will be the mapping provider for all of these companies.”
But not every automaker interested in maps is going it alone. BMW, Audi, and Mercedes, for example, are working together, pooling their data and handing it over to Here, a digital-map maker the three German companies acquired for $3.1 billion in 2015.
Kouri said he considered Here and its 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 installed on only 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 every day,” 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 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, though one major automaker is 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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