Self-driving car drove me from California to New York, claims ex-Uber engineer
Self-driving car drove me from California to New York,
claims ex-Uber engineer
Trip by Anthony Levandowski, controversial engineer
involved in Uber-Waymo lawsuit, would be longest without human taking over
Mark Harris Tue 18 Dec 2018 14.48 EST
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.
The 3,099-mile journey started on 26 October on the
Golden Gate Bridge, and finished nearly four days later on the George
Washington Bridge in Manhattan.
The car, a modified Toyota Prius, used only video
cameras, computers and basic digital maps to make the cross-country trip.
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. “If there was
nobody in the car, it would have worked,” he said.
If true, this would be the longest recorded road journey
of an autonomous vehicle without a human having to take control. Elon Musk has
repeatedly promised, and repeatedly delayed, one of his Tesla cars making a
similar journey.
A time-lapse video of drive, released to coincide with
the launch of Levandowski’s latest startup, Pronto.AI, did not immediately
reveal anything to contradict his claim. But Levandowski has little store of
trust on which to draw.
In 2017, Waymo accused him of stealing self-driving
secrets when he left Google to form another self-driving truck startup, Otto,
which was swiftly acquired by Uber. Levandowski pleaded the fifth hundreds of
time in depositions, although Uber settled the case (and fired Levandowski)
before he was called to testify in court. He has also been accused by
regulators in Nevada and California of illegally testing automated vehicles
there.
“I don’t really dwell on the past,” Levandowski told the
Guardian during a ride in the Prius along highways near Pronto’s San Francisco
offices last week. “At the end of the day, what matters is facts and reality.
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. Similar technology is already available for some
luxury cars, notably Tesla’s Autopilot, and it requires an alert human driver
to pay attention at all times.
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.
“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,” said Levandowski. Large truck crashes kill nearly 4,000
people each year in the US, according to Department of Transportation
statistics.
Ognen Stojanovski, a lawyer and research scholar at
Stanford University who co-founded Pronto, said, “Trucking is a tight-margin
business. 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. This is not because
he is afraid of more lawsuits, Levandowski insists, but because he now believes
that lidars are an expensive and unnecessary red herring in the quest for
robotic vehicles.
The fact that completely driverless cars do not yet exist
is not because lidar technology is not good enough, Levandowski said, but
because the software is not good enough.
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. Images from the
cameras are fed to the trunk, where a computer is running two neural networks:
artificial intelligence systems that can speedily process large quantities of
data.
One network recognizes lane markings, signs, obstacles
and other road users, and extracts information about their position and speed.
The second takes that information and controls the driving, using digital
signals and mechanical actuators for the throttle, brake and steering.
A seventh camera faces inwards, watching the human driver
to ensure that they are keeping their eyes on the road. Should the driver look
away, nod off, or pull out a cellphone, the system sounds increasingly strident
alerts and could ultimately be programmed to stop the vehicle. The Guardian saw
this system in operation.
Pronto will begin selling the Copilot in the first half
of 2019, initially as a $5,000 aftermarket installation for newer trucks.
Levandowski says the company will interview and then train prospective
customers so they know what the system can, and cannot, do.
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.
“There are more self-driving scenarios that we need to
handle than there are atoms in the universe,” said Levandowski. This is a
reference to the famously complex board game Go, at which Google’s AlphaGo AI
beat the best human players in 2016.
Copilot is still a long way off matching even an average
human driver, however. The highway-only system has not been trained to drive on
city streets, where pedestrians, cyclists, narrow roads and oncoming traffic
make driving exponentially more difficult.
During the Guardian’s 48-mile test ride, it drove safely
and competently, and succeeded in changing lanes several times on its own
initiative. However, at one point, Levandowski took the wheel after the car
failed to merge into busy traffic. Such hiccups are called disengagements in
the self-driving world. Levandowski attributed the disengagement to the latest
version of Pronto’s constantly evolving software.
Completing the transcontinental voyage also took multiple
attempts. The first try, in late September, ended on the Bonneville Salt Flats
in Utah, when the system disengaged on a banked curve in high winds. On its
second go, two weeks later, Levandowski says the Copilot worked perfectly for
650 miles, again as far as Utah. But it was too perfect for one Nevada highway
patrol officer, who pulled the Prius over after noticing it driving slightly
below the speed limit in an area where most drivers were speeding.
“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. So we came back to San
Francisco,” recalls Levandowski.
Pronto engineers adjusted the software so that the car
would be allowed to travel faster on certain roads, and tried again. On his
third trip, Levandowski said that he encountered rain in Nebraska and Illinois,
high winds in Wyoming, and a rolled-over semi in Pennsylvania, but eventually
made it to the George Washington Bridge without a disengagement.
“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. “Anthony’s job is to
make claims that may be at the edge of what his technology is capable of,” she
said. “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. “The real test is how repeatable it is,” said one. The
other added that Levandowski remains “radioactive” in the industry, and
speculated that he would find it difficult to raise funds because of his
checkered past.
Levandowski’s immediate task is less thorny: to sell a
small number of prototype Copilots and transfer the technology from Pronto’s
Prius to commercial trucks.
“I’ve learned a lot in the last couple of years about how
to do engineering, both on the technical side but also how to operate and be
more responsive to people’s criticisms,” said Levandowski. “We’re not promising
the moon. We want to promise things that are very concrete and that we can
deliver.”
Pronto.AI is not alone in wanting to reboot trucking.
Dozens of transportation startups are working on partially automated,
driverless and even remote control semis, with Levandowski’s former employer,
Waymo, already testing its own self-driving trucks in Georgia, California and
Arizona.
Despite re-entering such a crowded market, Levandowski
feels that his legal difficulties, at least, are now behind him. “I don’t
expect letters from any lawyers,” he said. “The technology has been built from
scratch and we have the logs to show every keystroke. It’s a totally new
approach.”
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