AI News, Waymo artificial intelligence

Self-driving car drove me from California to New York, claims ex-Uber engineer

Anthony Levandowski, the controversial engineer at the heart of a lawsuit between Uber and Waymo, claims to have built an automated car that drove from San Francisco to New York without any human intervention.

Levandowski told the Guardian that, although he was sitting in the driver’s seat the entire time, he did not touch the steering wheels or pedals, aside from planned stops to rest and refuel.

I’m very proud that we were able to achieve, in my mind, a pretty monumental self-driving milestone.” Pronto.AI will not be selling Levandowski’s new technology in a self-driving vehicle, nor using it for passenger cars at all.

Instead, it will form the basis of an advanced driver assistance system (ADAS) called Copilot, offering lane keeping, cruise control and collision avoidance for commercial semi-trucks.

Driving a truck is a really hard job, and we think Copilot can make it a lot easier on drivers, and reduce fatigue, while increasing safety Levandowski confirmed that he acted as a safety driver on Pronto’s coast-to-coast trip, ready to take over should the system have failed.

Driver retention is a huge cost, and if we can add even a little bit of safety, lower claims from less severe crashes will make a huge difference.” The system does not use laser-ranging lidars like those that Levandowski helped to develop at Waymo, Otto and Uber.

Pronto.AI’s driving technology uses only six video cameras, pointing to the front, side and rear of the vehicle, and each with a much lower resolution than those found in modern smartphones.

Pronto’s AI-powered approach allows Copilot to drive without the extremely detailed digital maps that many rival automated vehicle technologies require, Levandowski said, as well giving it the flexibility to respond intelligently to unfamiliar situations.

“The team tried to tell me that it wasn’t a disengagement, but I said, I can’t touch the steering wheel, brake or gas otherwise everybody’s going to look for the gotcha.

“If true, a truck that used only cameras to steer, brake, and accelerate for 100% of any cross-country trip is impressive,” said Bryant Walker Smith, a law professor at the University of South Carolina and member of the US Department of Transportation’s advisory committee on automation in transportation.

“Making a system work with cameras alone could be a major contribution, especially if this could be applied to higher levels of driving automation.” Missy Cummings, director of the Humans and Autonomy Laboratory at Duke University, remains deeply suspicious.

“I have not seen evidence of amazing breakthroughs that would be a game-changer in driverless car technology, particularly if it’s only relying on cameras.” The CEOs of two self-driving startups, who asked not to be identified, were also skeptical but agreed that such a trip would represent a significant advance.

Why Waymo’s Fleet of Self-Driving Cars Is Finally Ready for Prime Time

As our Chrysler Pacifica minivan readies to make a left turn through a four-way intersection in Mountain View, California, it suddenly pauses.

In the back seat, Dmitri Dolgov, Waymo’s chief technology officer and VP of engineering, an intense man of 40 whose speech bears a faint trace of his native Russia, looks perfectly calm.

Dolgov, whose own Waymo car ferried him to work today, as it does most days, has been with the company from the beginning, back when it was known as Google’s self-driving car project.

Two years ago, Google spun Waymo out into an independent company dedicated to developing and commercializing self-driving technology, though it hasn’t strayed far from its roots;

(Dolgov, then a postdoctoral fellow at Stanford, was a member of Junior’s team.) In the time since, Waymo’s cars have benefited from huge increases in onboard computing power and a sophisticated proprietary suite of sensors—radar, multiple cameras, three types of custom-designed lidar—most of which Waymo, now a subsidiary of Alphabet, Google’s parent company, builds itself.

Last year Waymo added a high-resolution, long-range sensor that, it is said, can pick out a football helmet two football fields away, plus a short-range vision system to allow for uninterrupted surround viewing—“down, behind, and next to the vehicle”—at all times.

And rather than simply outfitting old-fashioned cars with a hardware stack, as Waymo used to do, the technology is increasingly integrated on the assembly line with its host vehicles—mostly Chrysler Pacifica minivans and, soon, tens of thousands of Jaguar I-PACE electric SUVs that will be added to the company’s fleet in the coming years.

experimental tech project, with limited test runs on carefully chosen routes in sunny, wide-avenued cities across the country, Waymo’s fleet of 600 self-driving cars is now ready for prime time.

And the Phoenix-area service will soon go public, making it the world’s first autonomous-vehicle commercial taxi service, which riders will hail via an Uber-like app, launching by the end of the year.

This vision was what convinced Krafcik to come to Waymo after spending the bulk of his career in the traditional automobile industry, where he worked to advance technologies like antilock brakes and electronic stability control.

When a signal was added to let riders know the car was slowing for a crosswalk—a safety feature built into the system—“the perception of the action,”

In July, Waymo and the Phoenix-area transit authority announced a pilot program to allow transit workers (and in time, seniors and the disabled) to hail Waymo cars from their homes to light-rail stations and back.

The WIRED Guide to Self-Driving Cars

In the past five years, autonomous driving has gone from “maybe possible” to “definitely possible” to “inevitable” to “how did anyone ever think this wasn’t inevitable?” to "now commercially available."

The details of the program—it's available only to a few hundred vetted riders, and human safety operators will remain behind the wheel—may be underwhelming but don't erase its significance.

Countless hungry startups have materialized to fill niches in a burgeoning ecosystem, focusing on laser sensors, compressing mapping data, setting up service centers, and more.

This cycle has restarted, and the term “driverless car” will soon seem as anachronistic as “horseless carriage.” We don’t know how cars that don’t need human chauffeurs will mold society, but we can be sure a similar gear shift is on the way.

Just over a decade ago, the idea of being chauffeured around by a string of zeros and ones was ludicrous to pretty much everybody who wasn’t at an abandoned Air Force base outside Los Angeles, watching a dozen driverless cars glide through real traffic.

So, Darpa figured, maybe someone else—someone outside the DOD’s standard roster of contractors, someone not tied to a list of detailed requirements but striving for a slightly crazy goal—could put it all together.

Each team grabbed some combination of the sensors and computers available at the time, wrote their own code, and welded their own hardware, looking for the right recipe that would take their vehicle across 142 miles of sand and dirt of the Mojave.

But the race created a community of people—geeks, dreamers, and lots of students not yet jaded by commercial enterprise—who believed the robot drivers people had been craving for nearly forever were possible, and who were suddenly driven to make them real.

Within 18 months, they had built a system that could handle some of California’s toughest roads (including the famously winding block of San Francisco’s Lombard Street) with minimal human involvement.

And the proliferation of ride-hailing services like Uber and Lyft weakened the link between being in a car and owning that car, helping set the stage for a day when actually driving that car falls away too.

The tech giants followed, as did an armada of startups: Hundreds of small companies are now rushing to offer improved radars, cameras, lidars, maps, data management systems, and more to the big fish.

The key tool for doing that perception work—seeing the difference between a stray shopping cart and a person using a wheelchair, for example—is machine learning, which requires not just serious artificial intelligence chops but also gobs upon gobs of real-world examples to train the system.

That’s why Ford invested a billion dollars into artificial intelligence outfit Argo AI, why General Motors bought a startup called Cruise, why Waymo has driven 10 million autonomous miles on public roads (and billions more in simulation).

In November 2018, Tesla debuted a feature called Navigate on Autopilot, which gives its cars (including those already on the road, thanks to an over-the-air software update) the ability to change lanes to get around slower drivers or to leave the highway when it reaches its exit.

At least two Tesla drivers in the US have died using the system (one hit a truck in 2016, another hit a highway barrier this year), and the National Transportation Safety Board has criticized Tesla for making a system that's too easy to abuse.

The huge automakers that build millions of cars a year rely on the complex, precise interaction of dozens or hundreds of companies, the folks who provide all the bits and bobs that go into a car, and the services to keep them running.

Instead, expect to see these robocars either debut as highway-bound trucks or in taxi-like fleets, operating in limited conditions and areas, so their operators can avoid particularly tricky intersections and make sure everything is mapped in excruciating detail.

You know how fiercely Uber and Lyft fight for market share today, tracking drivers, trying to undercut each other, and piling up promotions to bring in riders?

It’s easy to conjure up a dystopia, a world where robocars encourage sprawl, everyone lives 100 miles from their job, and sends their self-driving servants to do their errands and clog our streets.

The optimists imagine a new kind of utopian city, where this technology not only eliminates crashes but integrates with existing public transit and remains affordable for all users.

We Drove In Google's Newest Self-Driving Car (HBO)

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