Aug 4, 2017 News of the Day: Volvo to Share Engine Tech With Geely, Mercedes Says Autonomous Cars Will Start as Taxis
【Summary】Aug 4, 2017 News of the Day
Volvo to Share Engine Tech With Geely
BEIJING — Sweden's Volvo Cars, a unit of Zhejiang Geely Holding Group, has agreed to make some engines available for Geely-branded vehicles, sources said, deepening ties between the carmakers who already share technology through third brand Lynk & Co.
Three people close to Geely and Volvo said the first Volvo-powered Geely model was expected to hit the market as early as late next year as a 2019 model year car.
The car will be equipped with a new 1.5-liter turbocharged gasoline engine which Volvo has been developing for smaller cars, the knowledgeable individuals said.
Volvo is expected to share a 2.0-liter turbocharged engine at a later date and will also allow Geely-branded cars to use a common vehicle platform the two automakers developed jointly for Volvo and Lynk & Co.
"The terms of the recently announced joint venture between Volvo Cars and Geely Group mean that existing and future technologies can be shared by Volvo, Geely Auto and Lynk & Co, under license agreements," a Volvo spokesman said.
As part of this deepened technology-sharing arrangement, Geely on Friday said it has completed the formation of a joint-venture with Volvo, called GV Automobile Technology Co, to "cooperate on automotive technologies, purchasing and the future development of" Lynk & Co, Geely said in a press release.
Earlier this year, Geely bought 49.9 percent of struggling Malaysian carmaker Proton from conglomerate DRB-HICOM Bhd. Geely officials have told Reuters the Hangzhou automaker is planning to improve Proton cars by sharing Geely and Volvo technologies.
Analysts have said one big risk for Volvo, as it combines more with its parent, is the dilution of Volvo's brand image by sharing its technology and know-how with a Chinese auto upstart.
Samuelsson told Reuters last month the deal would provide Volvo with greater development resources and efficiency in purchasing parts. It also should help Volvo speed up introduction of new technology in areas such as components for electric vehicles, he said.
Mercedes Says Autonomous Cars Will Start as Taxis
In an interview with Automotive News, Ola Kaellenius, Daimler's head of Group Research & Mercedes-Benz Cars Development, said he thinks self-driving taxis are the only way forward. Why? Because privately owned cars would be too expensive. At least in the beginning.
"The number of sensors you have to put on the car, the computing power and so on adds tens of thousands of dollars once you get it into production," said Kaellenius. "Where do you have a business case for something like that? You have it in a robot taxi scenario, where you can take a city or a part of the city and say, ‘OK, I'm going to put a hundred, 200, 300, a thousand … into this area.'" By providing a taxi service instead of selling cars privately, he thinks Mercedes could actually start to make money pretty quickly.
"The amortization comes through not paying the driver. You could have a very quick amortization, so our effort on Level 4, 5 is robot taxi first. In our case the commercialization of that happens between 2020 and 2025 where we start rolling that out — either through our own mobility services that we're building up or as a partner with other mobility services," said Kaellenius.
After that, if the cost of autonomous technology comes down and consumer interest is high enough, you may see Mercedes sell self-driving cars directly to consumers. But unless Kaellenius has it wrong, it'll probably be a long time before you can buy a Mercedes that can truly drive itself.
Chevy Bolt EV Beats Tesla Model S 75D in Consumer Reports Test
On paper, the Tesla Model S 75D has more range than the Chevy Bolt. The Bolt gets an EPA-estimated 238 miles of driving range on a single charge, while the Tesla is rated at 259 miles. According to testing from Consumer Reports, though, in a head-to-head comparison the Bolt outperforms the Tesla Model S 75D, even surpassing its own range rating by 12 miles.
In CR's test, the Bolt went 250 miles before running out of juice. The 2016 Tesla Model S 75D went just 235 miles, underperforming its own rating, and even the lesser rating of the Bolt. The 2016 Tesla Model X 90D, rated at 257 miles, also petered out early, at just 230 miles. CR hasn't yet tested the 100D variants of the Model S and Model X, but says those would likely drive further than the Chevrolet Bolt. Still, either of those would cost at least $100,000 (before the federal tax credit), while the Bolt starts at just $37,495.
Based on the results of its testing, Consumer Reports ranks the Chevy Bolt as the second best all-electric vehicle, behind the Model S. Besides range, the Chevy scores well for agility and quietness, but suffers because of its "squishy" brake feel, charging time, bumpy ride, and less-than-spectacular seats.
Researchers Trick Self-Driving Cars to Mislabel Road Signs
University of Washington have shown they can get computer vision systems to misidentify road signs using nothing more than stickers made on a home printer. UW computer-security researcher Yoshi Kohno described an attack algorithm that uses printed images stuck on road signs.
These images confuse the cameras on which most self-driving vehicles rely. In one example, explained in a document uploaded to the open-source scientific-paper site arXiv last week, small stickers attached to a standard stop sign caused a vision system to misidentify it as a Speed Limit 45 sign.
The vision systems in autonomous cars typically have an object detector and a classifier: the former spots pedestrians, lights, signs, and other vehicles, and the latter decides what the object is and what the signs are saying. The attacks Kohno described assume that hackers are able to gain access to this classifier and then, using its algorithm and a photo of the target road sign, generate a customized image.
The attack relies on the vulnerability of deep neural networks that have been trained to recognize signs, stoplights, and other road users using images from cameras mounted on self-driving vehicles. These systems can be sensitive to malicious perturbations—small, precisely crafted changes to their inputs—that can cause them to misbehave in unexpected and potentially dangerous ways.
Researchers have long known that tinkering with what a computer sees can lead to incorrect results. But previous attacks involved changes that were either too extreme—and thus obvious to human drivers—or too subtle, only working from a particular angle or at a certain distance.
In this example, researchers printed out a true-size image similar to the Right Turn sign and overlaid it on top of the existing sign. Subtle differences cause this to be read as a Speed Limit 45 sign.
The algorithms created by Kohno and colleagues at the University of Michigan, Stony Brook University, and the University of California are designed to be printed on a normal color printer and stuck to existing road signs.
One attack prints a full-size road sign to be overlaid on an existing sign. In this example, the team was able to create a stop sign that was consistently classified by a computer vision system as a Speed Limit 45 sign.
A second exploit used small, rectangular black-and-white stickers that, when attached to another stop sign, also caused the computer to see it as a Speed Limit 45 sign. The attacks were successful at a variety of distances, from close up to 40 feet away, and at a range of angles.
Using an attack disguised as graffiti, researchers were able to get computer vision systems to misclassify stop signs at a 73.3% rate, causing them to be interpreted as Speed Limit 45 signs.
"We [think] that given the similar appearance of warning signs, small perturbations are sufficient to confuse the classifier," wrote Kohno and his colleagues. "In future work, we plan to explore this hypothesis with targeted classification attacks on other warning signs."
The dangers of such attacks are clear. Many experimental self-driving cars and some production vehicles, including Tesla's entire range of electric cars, can already automatically recognize road signs. If a future self-driving vehicle could be tricked into responding incorrectly to a sign, it could be made to blow through a stop sign or slam on its brakes in the fast lane.
Aurora Innovation Applies for Autonomous Testing Permit in California
Aurora Innovation is the latest start-up to receive an autonomous car testing permit from the California Department of Motor Vehicles. Aurora is the 37th organization to receive one of these permits, according to Fortune. Aurora joins automakers like Ford, Tesla, Honda, and General Motors, tech companies like Uber, Waymo, and Apple, as well as Chinese automaker SAIC.
Aurora is based in Silicon Valley and led by Sterling Anderson, the former director of Tesla's Autopilot program, and Chris Urmson, the former head of Google's self-driving car project. Also onboard is Drew Bagnell, who previously ran the autonomy and perception team at Uber's Advanced Technologies Center. The lineup of executives lends some credibility to Aurora—but it's still unclear what the company's plans are, or how Aurora will distinguish itself from the numerous other companies working on autonomous driving.
Aurora told Fortune that it is already testing self-driving cars on closed courses, but did not say when testing on public roads would begin. It also hasn't disclosed how many cars it plans to test, or what makes and models it will use. In April, the company said it would use a 2017 Audi Q7 as a data-gathering platform.
Aurora reportedly plans to develop virtually everything needed for autonomous driving except the cars themselves. That includes a full suite of sensors, the software needed to enable autonomous driving, and the data infrastructure to support it. The company will likely partner with automakers to commercialize its technology.
Originally from New Jersey, Eric is an automotive and technology reporter specializing in the high-tech industry in Silicon Valley. Eric has over fifteen years of automotive experience and a B.A. in computer science. These skills, combined with technical writing and news reporting, allows him to fully understand and identify new and innovative technologies in the automotive industry and beyond. He has worked on self-driving cars and as a technical writer, helping people to understand and work with technology. Outside of work, Eric likes to travel to new places, play guitar, and explore the outdoors.
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