Tuesday, March 12, 2019

I don't say enough nice things about Ars Technica -- AV Edition

This recent piece is a must read for anyone following this story byTimothy B. Lee

Tesla is clinging to an old conventional wisdom

In 2014, the same year Tesla started shipping the first generation of Autopilot hardware, the Society of Automotive Engineers published a five-level taxonomy of autonomous driving systems that envisioned driver-assistance systems (known as "level 2" in SAE jargon) gradually morphing into fully autonomous systems that could operate without human supervision (levels 4 and 5).
But the last five years have seen a dramatic shift in industry thinking. Most companies now see driver assistance and full self-driving as distinct markets.

No company has done more to change industry thinking here than Google, whose self-driving project was spun off as Waymo in 2016. Around 2012, Google engineers developed a highway driving system and let some rank-and-file Googlers test it out. Drivers were warned that the system was not yet fully autonomous, and they were instructed to keep their eyes on the road at all times.
But the self-driving team found that users started to trust the system way too quickly. In-car cameras showed users "napping, putting on makeup and fiddling with their phones." And that created a big safety risk.

"It's hard to take over, because they have lost contextual awareness," Waymo CEO John Krafcik said in 2017.

So Google scrapped plans for a highway driver assistance product and decided to pursue a different kind of gradualism: a taxi service that would initially be limited to the Phoenix metropolitan area. Phoenix has wide, well-marked streets, and snow and ice are rare. So bringing a self-driving service to Phoenix should be significantly easier than developing a car with self-driving capabilities that work in every part of the country and all weather conditions.

This approach has some other advantages, too. Self-driving cars benefit from high-resolution maps. Gathering map data in a single metro area is easier than trying to map the whole world all at once.
Self-driving cars also benefit from lidar sensors, and the best ones cost thousands—if not tens of thousands—of dollars each. That's too expensive for an upgrade to a customer-owned vehicle. But the economics are more viable for a driverless taxi service, since the self-driving system replaces an expensive human taxi driver.

Over the last three years, most other companies working on self-driving technology have followed Waymo's lead. GM bought a startup called Cruise in 2016 and put it to work developing an autonomous taxi service in San Francisco. Ford made a similar bet on Argo AI in 2017—the company is now developing autonomous taxi services in Miami and Washington DC.
Volkswagen and Hyundai have deals with Aurora—a startup co-founded by Chris Urmson, the former leader of the Google self-driving project—to develop fully autonomous taxi services. Technology companies like Uber and Zoox are planning to introduce autonomous taxi services.

Tesla’s business model locks it into the old approach

Tesla, meanwhile, has stubbornly pushed forward with its original strategy. For more than two years, Tesla charged customers $3,000 or more for a "full self-driving" package. But progress has been slow. And that has put Tesla in a bind. Abandoning the old strategy would likely require refunding customers who paid for the Full Self-Driving package—which would be both embarrassing and expensive.

Instead, Tesla's solution has been to move the "full self-driving" goal posts.

"We already have full self-driving capability on highways," Musk said during a January earnings call. "So from highway on-ramp to highway exit, including passing cars and going from one highway interchange to another, full self-driving capability is there."
Obviously, this statement comes with a big asterisk: the driver still has to supervise the car to make sure it doesn't crash.

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