Thanks to a dashcam, crafty Uber drivers are boosting their pay

For Uber and Lyft drivers, installing a dashboard camera can boost their earnings by 5% to 15%.

Drivers are starting to place cameras behind their windshields to record the road ahead of them. Startups chasing the gold mine of car data are paying them to install these cameras. The startups want these videos to do everything from build maps for self-driving cars to track pedestrian activity.

 

A San Francisco startup, lvl5, is crowdsourcing maps for autonomous vehicles from dashcam videos. Two of its founders previously worked on Tesla’s autopilot team.

In three months, they’ve mapped over 500,000 miles of U.S. roads with 2,000 drivers using their iPhone app, Payver. Drivers receive between two and five cents per mile. Lvl5 expects that with 50,000 U.S. drivers, it can gather enough data to build maps for self-driving cars.

Lvl5 was founded in December by Andrew Kouri and Erik Reed, who both worked on Tesla’s Autopilot team, and George Tall, a computer vision engineer from iRobot, has developed a way to take enormous amounts of video collected from a camera and turn it into high-definition 3D maps that are constantly refreshing. These maps will always reflect the latest road conditions, providing self-driving cars with the information they need to detect and plan their route safely.

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“The thing that everyone is kind of ignoring silently is that self-driving cars won’t ship unless we have really good HD maps that update every single day,” Kouri said in an interview with The Verge. “And nobody has a system to do this yet. This is what we’re building.”

Kouri says self-driving cars don’t need LIDAR, light detection, and ranging radar used to see the world around it. That’s a departure from what many automakers and tech companies like Google’s Waymo say is needed for the safe deployment of autonomous vehicles.

Lvl5’s philosophy, in many ways, mirrors Tesla’s approach, which contends it can deploy fully autonomous vehicle technology without relying on LIDAR.

“We don’t really care if LIDAR wins out or computer vision wins out,” Kouri said. “Right now we know that if we want to make self-driving car en masse, cameras are ready and LIDAR is not.”

The company’s system uses consumer-grade cameras and a computer vision algorithm to turn all of the video it captures into useable, 3D maps. But it needed to scale it.

So they reached out to Uber and Lyft drivers who can crowdsource the video data via a dashcam app created by Lvl5 called Payver.

Drivers are paid to mount smartphones on the dashboard of their cars and run the app, which automatically collects video, accelerometer, and GPS data. Huge amounts of data are captured; video is taken every meter along a vehicle’s route. The compressed data is then sent to the cloud and then sent to lvl5’s central hub. From there, lvl5 uses its computer vision algorithm to translate all of this footage into high-definition 3D maps.

Source:

https://www.theverge.com/2017/7/19/16000272/lvl5-self-driving-car-tesla-map-lidar

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