The Director of Tesla’s Autopilot program, Sterling Anderson, spoke at the recent MIT Technology Review EmTech Digital conference in San Francisco on May 24. In the presentation, he made a number of interesting comments.
During the event, Anderson revealed that, following the beginning of Autopilot hardware installations back in late 2014, and up until the launch of the feature in late 2015, the company downloaded data relating to literally millions of miles worth of owner driving.
This extensive data — revealing the driving habits of owners, road conditions, etc — is what allowed the company to so rapidly launch such a superior product (as compared to competitors), according to Anderson.
“The ability to pull high-resolution data from these vehicles and to update the vehicles over the air is a significant part of what’s allowed us in 18 months to go from very behind the curve to what is today one of the more advanced autonomous or semi-autonomous driving features,” stated Anderson.
“Since introducing this hardware 18 months ago we’ve accrued 780 million miles,” Anderson continued. “We can use all of that data on our servers to look for how people are using our cars and how we can improve things.”
He also revealed that, at current fleet size, the company collects about a million miles worth of data roughly every 10 hours.
The really interesting part of his comments, though, is relating to how the company tests out new features. Gas 2 provides more:
Anderson also said something even more surprising. When Tesla engineers come up with new software ideas, they can be tested by uploading them to customers’ cars without them knowing about it. Then the company can monitor how the tweaks perform in real world driving before deciding whether to activate the new features via an over the air update.
“We will often install an ‘inert’ feature on all our vehicles worldwide,” said Anderson. “That allows us to watch over tens of millions of miles how a feature performs.” While ‘inert’, the software has no ability to actually control any of the functions of the car.
Anderson said Tesla’s data-driven strategy allows the company to keep advancing the company’s Autopilot technology. It will allow the system to operate more effectively in urban driving environments that have challenges like intersections, pedestrians, and other less predictable factors.
A very interesting approach. And one that to my eyes seems superior to the one being pursued by Google. Though, in Google’s case, the Tesla-approach wasn’t really an approach — owing to the company’s lack of a deployed fleet of vehicle to monitor.
Related:
Tesla Has The Right Approach To Self-Driving Cars
Tesla Autopilot Outdistances Google Cars
Images via LinkedIn/Sterling Anderson & Tesla Motors
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