Idriverplus: Building Smart Autonomous Vehicles with Velodyne Lidar Technology

Idriverplus: Building Smart Autonomous Vehicles with Velodyne Lidar TechnologyMay 21, 2019|In Blog|By Velodyne LiDAR
Interview with Dr.
Zhang Dezhao, CEO of Idriverplus

Viggo, IdriverPlus Street Sweeping Robot

Founded
in 2015, Idriverplus is the first company in China to launch the
commercialization of driverless technology. Velodyne Lidar has strategically
teamed with Idriverplus to help their efforts for the mass production of
commercial autonomous vehicles, which include passenger cars, street cleaners,
and logistics vehicles.

Led by
CEO Dr. Zhang Dezhao, Idriverplus’ driverless vehicles have accumulated test
mileage exceeding 400,000 kilometers, far surpassing other domestic autonomous car
manufacturers.

To
learn more about Idriverplus and their exciting vision for driverless vehicles,
we asked Dr. Zhang to discuss the company’s innovative autonomous driving
products and how Velodyne technology factors into their product strategy.

Dr. Zhang Dezhao, CEO of Idriverplus

Q: Idriverplus is an innovator in autonomous
vehicles. Please share with our readers some background on your company.

A:
Idriverplus is committed to becoming the world’s leading provider of
intelligent vehicle technology solutions. We have been focused on developing
the “brain” of a self-driving car. Our major R&D achievements have been in
unmanned distribution logistics vehicles, unmanned sanitation vehicles,
self-driving passenger cars, and more.

Q: Let’s look at each product
area for Idriverplus. How is your company addressing logistics and
distribution?

A: Our product called WOBIDA applies
self-driving technology to the logistics and distribution industry. We created
an automatic driving system combined with a cloud platform management system
for the intelligence required in the last kilometer of logistics distribution.
WOBIDA provides 360-degree whole-process monitoring and real-time information
interaction as well as an intelligent storage cabinet for transporting goods.
It delivers improved efficiency of logistics distribution and provides users
with a safer and better distribution experience.

Q: Please
discuss your unmanned street cleaning vehicles and where they are being used
now.

A: Our cleaning
vehicle is named Viggo. Idriverplus developed this unmanned system for a purely
electric solution to intelligently sweep roads. During the cleaning process, Viggo
can automatically track and avoid obstacles with stable and reliable
performance and monitor real-time vehicle information.

At present, Viggo has been used
in universities, factories, parks, an amusement park and city streets. It has
been deployed in Beijing, Tianjin, Shanghai, Hebei, Zhejiang, Henan, Hunan and
other provinces and cities with more than 100 units in operation. Additionally,
Idriverplus has strategic cooperation partnerships in Singapore, Dubai,
Malaysia, and other areas in Asia.

Idriverplus Autonomous Fleet

Q: What
has been the response from communities that have seen the unmanned street
cleaning vehicles?

A: According
to residents, Viggo not only improves cleaning efficiency, but also elevates
the appearance of the whole community. We are finding that children are
generally curious about self-driving cars – especially Viggo.

Q: Tell
us about the commercial autonomous car solution you are developing?

A: We currently have two
main development paths we are pursuing. One is an SAE Level 4 vehicle that
provides autonomous driving in closed parks and some public roads. We are also
developing an advanced driver assistance system (ADAS) solution, mainly for AVP
(automatic parking) and HWP (highway follow-up).

Q: How
do you see Idriverplus AV products benefiting businesses and communities?

A: We
have a vision for the future that autonomous driving is not only a means of
transportation, but also a necessity of life. In logistics and distribution, we
are committed to improving the logistics of the last kilometer. In sanitation,
we are committed to helping cleaners improve their work efficiency. In the area
of passenger cars, we are committed to building the strongest self-driving
brain for safer roadways.

Q: Why
did Idriverplus decide to use Velodyne lidar technology and what value do
Velodyne sensors add to Idriverplus vehicles?

A: Velodyne
Lidar’s products have better performance and stability in practical use, and their
accuracy addresses demanding requirements. Lidar is indispensable for the
development of autonomous driving technology. Technically, lidar’s perception
capabilities are mainly used in laser mapping and positioning a car in its
surrounding environment. Lidar is unlikely to be replaced in the long term. A
more likely direction will be to combine lidar with other sensors, also known
as multi-sensor fusion. As autonomous products are put on public roads, the
platform will be strengthened by having some redundancy capability. In this
case, the sensor solution is fusion, not substitution.

Q: What
is next for Idriverplus in using Velodyne technology?

A: We will use Velodyne’s advanced Velarray solution in our development program to build a solid foundation for mass production of an autonomous vehicle.

For Velodyne products click HERE

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Tesla’s Trouble With Semi Trucks & Another Shakeup Of The Autopilot Team — Is There A Connection?

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Published on May 21st, 2019 |

by Steve Hanley

Tesla’s Trouble With Semi Trucks & Another Shakeup Of The Autopilot Team — Is There A Connection?

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May 21st, 2019 by Steve Hanley

Editor’s note: Context is always worth keeping in mind. The following story is interesting and important, but in the grand scheme of traffic safety, one should consider not only the two deaths mentioned here, but also how many lives Tesla Autopilot has saved — which is likely a much higher number than two.

On March 1, Jeremy Banner was killed on a Florida highway when his Tesla Model 3 slammed into a tractor trailer that was crossing the road. The National Transportation Safely Board sent a team of investigators to find out more about the crash. Last week, it released this preliminary report.

Credit: NTSB

“Preliminary data from the vehicle show that the Tesla’s Autopilot system — an advanced driver assistance system (ADAS) that provides both longitudinal and lateral control over vehicle motion — was active at the time of the crash. The driver engaged the Autopilot about 10 seconds before the collision. From less than 8 seconds before the crash to the time of impact, the vehicle did not detect the driver’s hands on the steering wheel. Neither the preliminary data nor the videos indicate that the driver or the ADAS executed evasive maneuvers.”

The circumstances surrounding this fatality and the crash that killed Joshua Brown when his Tesla Model S also collided with a tractor trailer crossing a Florida highway three years ago are troubling. Why does Tesla’s vaunted Autopilot system have such difficulty recognizing an 18 wheeler crossing the road in front of it?

The Verge reports that a spokesperson for Tesla phrased what happened slightly differently. Instead of saying “the vehicle did not detect the driver’s hands on the steering wheel,” that person said, “the driver immediately removed his hands from the wheel.” Tesla did not respond to a request from The Verge to explain what action it plans to take to address the problem of a semi truck crossing a car’s line of travel.

Why Can’t Computers Think Like Humans?
The issue is the same for all self-driving cars — how do you make them behave like human drivers when that should be the minimum (and better than humans at other times)? People in Phoenix report that they are sick to death of Waymo’s self-driving cars faltering at intersections, unsure what to do. Because they have been programmed to err on the side of caution at all times, they wait an inordinate amount of time at stop signs, checking to make sure there is a clear path ahead before moving forward. Drivers waiting behind get exasperated and start blowing their horns or zoom around the obstructionist vehicles, creating unsafe traffic situations for others. It’s kind of silly to blow your horn at a computer that has no auditory input, but there you are.

It’s not that the Tesla Autopilot system doesn’t see trucks crossing in front. The issue is that it has been programmed to ignore them. As we drive down the road, our brain easily distinguishes between a tractor trailer and an overpass, but that is difficult for a computer to do. If it decides to slam on the brakes every time it approaches a highway overpass, that’s not good. To a computer, a truck trailer and a highway overpass look too similar, so the program tells it to ignore both, with predictable results.

Raj Rajkumar, an electrical and computer engineering professor at Carnegie Mellon University, has some insight into this this situation. Other than Tesla itself, Carnegie Mellon is ground zero for autonomous driving development in the world. He tells The Verge that in most road situations, there are vehicles to the front, back, and to the side, but a perpendicular vehicle is much less common. The algorithms using the camera output need to be trained to detect trucks that are perpendicular to the direction of the vehicle.

“Essentially, the same incident repeats after three years,” Rajkumar says. “This seems to indicate that these two problems have still not been addressed.” Machine learning and artificial intelligence have inherent limitations, he explains. If sensors “see” what they have never or seldom seen before, they do not know how to handle those situations. “Tesla is not handling the well-known limitations of AI,” he added.

Some Input From The Real World
Twitter user GreenTheOnly has some interesting input on this situation which he posted on March 13, nearly two weeks after Jeremy Banner died.

He reports his Tesla is running firmware version 19.8.1, and 25 seconds of video show the truck crossing his path and what happened afterwards — available in a subsequent tweet.

Driver Overconfidence
In the past, Tesla CEO Elon Musk has blamed crashes involving Autopilot on driver overconfidence. “When there is a serious accident it is almost always, in fact maybe always, the case that it is an experienced user, and the issue is more one of complacency,” he said last year.

That may be true of the current generation of Autopilot-equipped cars but it is not nearly good enough for the level of autonomy Musk boasted about during the recent Autonomy Day event when he said every Tesla equipped with the latest-generation autonomous driving hardware and the company’s new self-driving computer would be able to operate with almost no input from a human driver soon. “A year from now, we’ll have over a million cars with Full Self Driving computer, hardware, everything.”

He went on to say, “We expect to be feature complete in self driving this year, and we expect to be confident enough from our standpoint to say that we think people do not need to touch the wheel and can look out the window sometime probably around … in the second quarter of next year. And we expect to get regulatory approval, at least in some jurisdictions, for that towards the end of next year. That’s roughly the timeline that I expect things to go on.”

Skeptics Abound
There are plenty of skeptics. Writing in Forbes, Lance Eliot, a recognized authority in artificial intelligence and self-driving cars, says, “To some, it would be like running a marathon, which the best in the world can do in about 2 hours, and suddenly suggesting that you’ll be at the finish line in just thirty minutes, somehow skirting past all known laws of nature and physics. It’s a jaw dropping kind of declaration, especially if there isn’t any substantive evidence showcased to support a potential world-record-breaking projected achievement. At this point, it’s a wait-and-see status.”

The issue for Tesla and all self-driving systems is one of false positives. Radar outputs of detected objects are sometimes ignored by the vehicle’s software to deal with the generation of “false positives,” said Raj Rajkumar, an electrical and computer engineering professor at Carnegie Mellon University. Without these, the radar would “see” an overpass and report that as an obstacle, causing the vehicle to slam on the brakes.

On the computer vision side of the equation, the algorithms using the camera output need to be trained to detect trucks that are perpendicular to the direction of the vehicle, he added. In most road situations, there are vehicles to the front, back, and to the side, but a perpendicular vehicle is much less common.

“Essentially, the same incident repeats after three years,” Rajkumar said. “This seems to indicate that these two problems have still not been addressed.” Machine learning and artificial intelligence have inherent limitations. If sensors “see” what they have never or seldom seen before, they do not know how to handle those situations. “Tesla is not handling the well-known limitations of AI,” he added.

Autopilot Team Reshuffle?
We may never find out whether the death of Jeremy Banner is in any way connected to rumors on Reddit that Elon is reshuffling the Autopilot team and personally taking over its management. (Note: he has already led a weekly Autopilot team meeting for a few years.)

Remember what happened after the Joshua Brown fatality. Within months, Tesla and Mobileye went through a messy divorce, and Tesla had to spend a good chunk of time building its own Mobileye-like system. In this latest case, what will the ramifications be for Tesla, and the world?

Fatalities & Robotaxis
No firm conclusions can be drawn at this point, except to say that the final report from NTSB could put a crimp in Musk’s promise that Tesla robotaxis could make it into a $500 billion company in a few years. If regulators get cold feet about approving the use of self-driving Teslas for revenue service, that aspect of Musk’s long-term plans may get put on hold indefinitely.

Make no mistakes — the long knives are out and ready to stab Tesla in the back if the opportunity presents itself. With Tesla continuously leading it, the EV revolution could be set back years or even decades, especially in the US where fossil fuel interests with unlimited resources control the federal government and many states. We know one key component of any plan to reduce carbon emissions is to electrify everything, starting with the transportation sector. It is important, in my opinion, that the desire for self-driving cars not delay that process.

About the Author

Steve Hanley Steve writes about the interface between technology and sustainability from his home in Rhode Island and anywhere else the Singularity may lead him. His motto is, “Life is not measured by how many breaths we take but by the number of moments that take our breath away!” You can follow him on Google + and on Twitter.

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