The father of the 23-year-old Tesla driver who died in the crash filed the lawsuit in July in a Beijing court. The suit alleges that the accident, which occurred in January in the northeastern province of Hebei, was the fault of Tesla’s advanced driver assistance system (ADAS), according to Chinese state broadcaster CCTV.
Tesla confirmed this week it is investigating the fatal crash, but said it has no way of knowing if Autopilot was engaged due to the amount of damage the vehicle sustained. The driver, Gao Yaning, had borrowed his father’s Model S.
China’s CCTV published dashcam footage from the vehicle slamming into a street-sweeping truck in the far left lane of a highway.
In July, Mobileye announced it was ending its relationship with Tesla after a high-profile Model S fatality that occurred while Autopilot was engaged. The vehicle slammed into the side of an 18-wheel semi-tractor trailer truck that turned left in front of it on a divided highway.
Autopilot uses both radar and camera vision systems to discern objects in the path of a moving vehicle. Since rolling out Autopilot in 2014, however, Tesla drivers have publicized many videos showing them disengaged with their vehicles, allowing the ADAS technology to have complete control.
Yesterday, Shashua clarified why the company ended its relationship with Tesla.
“No matter how you spin it, (Autopilot) is not designed for that. It is a driver assistance system and not a driverless system,” Shashua said.
On Sunday, Tesla announced refinements to its Autopilot software. Among “dozens of small refinements” Autopilot Version 8 contains a more advanced signal processing algorithm “to create a picture of the world using the onboard radar.”
Alex Lidow, founder and CEO of Efficient Power Conversion (EPC), said that while radar may be useful in semi-autonomous and fully autonomous vehicles, LiDAR (Light Detection and Ranging) technology is far more accurate. LiDAR uses multiple lasers to create 3D scans of objects around a vehicle.
EPC makes semiconductors based on Gallium Nitride that the company claims are hundreds of times faster than traditional silicon chips. LIDAR manufacturers are using EPC’s chips because their fast speed enables LIDAR systems to paint a much clearer picture of objects in the road.
Radar, Lidow said, offers too low a resolution picture for ADAS systems to accurately discern all the objects in the path of a moving car, so cameras are needed in addition as part of a meshed “vision system.
Lidow said there’s simply no contest when it comes to comparing radar and lasers for autonomous driving systems.
LiDAR uses up to 64 lasers to send out a pulse of 30,000 photons, and as few as two returning photons in less than 10 nanoseconds (a nanosecond is a billionth of a second) can be used to determine if an object is in the path of a moving vehicle.
“For example, if a pulse returns in 10 nanoseconds, that means the object is 5 feet in front of you,” Lidow said. “Pulses are 4 nanoseconds wide, so each laser beam can send 250 million pulses a second, and with 64 lasers that means the car is receiving billions of pixels a second to form an image. That high resolution 3D image is unambiguous and not open to interpretation.
Tesla CEO Elon Musk has gone on record saying he doesn’t think his all-electric vehicles need LiDAR, and argues that passive forward-looking radar can accomplish ADAS functions.
“I think that completely solves it without the use of LIDAR. I’m not a big fan of LIDAR, I don’t think it makes sense in this context,” Musk said last year.
Lidow, however, believes LiDAR on semi-autonomous and autonomous vehicles will eventually be as common as anti-lock brakes or airbags in vehicles today.
Quanergy Systems, Velodyne LiDAR and Israeli startup Innoviz have already promised that by 2018 they will have sub-$250 LiDAR systems based on a single solid-state chip. Start-up Scanse recently ran a Kickstarter campaign and raised more than $272,000 toward bringing a $250 LiDAR unit to market.
“I think we’re probably five to eight years away from a highly integrated LiDAR system,” Lidow said. “It’s a Catch 22. Integration makes sense when have high volume and high volume happens when you have low cost. And only high integration leads to low cost.”
SOURCES- Computer World, Quanergy, Delphi, Youtube
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.