AEye Team Profile: Vivek Thotla

On June 26th, AEye Staff Engineer, Vivek Thotla, will be speaking on a panel called “Should We Take CV To The Edge?” at IoT Forum on Computer Vision @ Sensors Expo.
Vivek is a staff engineer at AEye, where he leads product verification and validation, and is responsible for LiDAR simulation and data strategy in producing automotive grade products. Previously, he was a Component Owner / Functional Delivery Owner for point cloud algorithms at Continental, where he was responsible for planning, requirements, design and development of embedded platform-based algorithms for a Hi-Res 3D Flash LiDAR, in addition to enforcing ADAS process stages to meet ASPICE levels and functional safety. He has also held engineering roles at Tribis, AmpliSine Labs, Missouri S&T and Enigma Portal. Vivek holds an MBA in Information Technology Project Management and a PhD and Masters in Electrical, Electronics and Communications Engineering.

We sat down with Vivek to learn more about the advantages of integrating computer vision at the sensor, building automotive grade LiDAR products, and why he decided to move to the Bay Area.

Q: How much of an autonomous vehicle’s computer vision should be done at the sensor, as opposed to a central processor?
The amount of data produced today by a perception system is enormous. And incorporating all the data from the different kinds of sensors used (like radar, camera, and LiDAR) makes it very difficult and expensive to process and store. In a typical perception system, roughly 80% of the data produced by the sensors is thrown out.

However, intelligent sensors – like what we develop at AEye – are software definable. Meaning, you can adjust its settings to get high resolution data from an object and get sparse data in the background, cutting down the overall amount of data processed by more than 80%. This makes computer vision algorithms at the central processor faster and efficient because once you preprocess data, latency becomes less of an issue. Currently, AV companies are spending a tremendous amount of money storing useless data. Preprocessing saves both time and money.

Q: What is the largest challenge in producing automotive grade LiDAR products?
Industry wide, the greatest challenge is maintaining the quality, reliability, and consistency needed on all components and software that go into a LiDAR sensor of over 100,000 samples or more and over the sensor’s lifetime. Another major challenge for bringing LiDAR products to the automotive market is designing the sensor to fit in different regions of the car. There are a lot of constraints based on where the sensor is placed on the vehicle and certain issues that arise from each placement. For example, a sensor placed behind a windshield might need a completely different design than a sensor that’s placed in the front bumper.

There are many interesting LiDAR architectures out there that work really well at smaller samples and in the lab. But the moment the product needs to scale and deal with all the quality and environmental requirements of being an automotive grade product, they fail. AEye is mitigating these challenges by partnering directly with Tier 1’s who know the process of making large-scale, automotive grade products. In my own experience, I’ve found that once a Tier 1 partners with you, they are extremely supportive because they believe in you, and that proves you are capable of achieving it.

In addition to our partners who help us push the sensor to automotive grade, we have a great functional safety team here at AEye. I came to AEye from a Tier 1, so I know what goes into developing an automotive grade sensor, and the AEye team is made up of people from all over the automotive industry that have great, diverse insight into how to bring a product to market.

Q: You moved to the Bay Area from Santa Barbara. What was it about Silicon Valley that drew you here?
It has always been my dream to come to Silicon Valley – you hear about it so much as the epicenter of technology and innovation. And it’s true: Silicon Valley is at the heart of the autonomous driving industry. All the innovative and novel work happening today in the LiDAR industry is happening here and I did not want to miss my chance to help develop the tools for true autonomy.

Connect with AEye at Sensors Expo! Learn more here.

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A Qashqai Is Nissan Sunderland’s 10 Millionth Vehicle

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A Qashqai Is Nissan Sunderland’s 10 Millionth Vehicle

20 Jun 2019, 20:18 UTC ·
by Mircea Panait

Home > News > Industry

Founded in 1984, Nissan Motor Manufacturing UK is headquartered in Sunderland. Built on the site of a former RAF airfield, the factory where the Qashqai is manufactured is complemented by the Japanese automaker's distribution center and lots of on-site suppliers.
21 photos
Production at Sunderland started in 1986 with the Bluebird, then the Primera and Micra followed in 1990 and 1992. As of May 2019, the Micra and Primera are listed on second and third in terms of total production at the British plant. The Qashqai reigns supreme even though it’s been introduced in 2006, tallying more than 3,416,500 examples of the breed.
33 years on, Nissan Motor Manufacturing UK reaches the ten million mark with a Vivid Blue-painted Qashqai Tekna. The vehicle is optioned with ProPilot semi-autonomous driving technologies. “Building ten million vehicles is a tremendous achievement for everyone associated with the plant,” said Steve Marsh, vice president of manufacturing at Sunderland.
“Together we are determined to continue to drive up the high quality standards our customers have come to expect over the last three decades,” concluded the official, but we don’t agree with everything. For starters, continuously variable transmissions built by JATCO are as unreliable as CVTs get. There’s also the matter of Renault, which took its toll on build quality ever since the alliance was formed.
The Infiniti Q30 is also manufactured in Sunderland, a Mercedes-Benz GLA-Class with a different body shell, interior, and badging. Does it come as a surprise this crossover isn’t selling well? The luxed-up brand is leaving the western part of Europe in 2020 because of poor sales, totaling 5,800 vehicles in 2018.
Turning our attention back to production, Sunderland is also the place where the Leaf is manufactured for the United Kingdom and Europe. The all-electric hatchback is joined by the Juke, which will enter the second generation for the 2020 model year.
Parked bumper to bumper, Nissan claims the 10 million vehicles manufactured in Sunderland would stretch around the globe. Considering that Earth has a circumference of 40,075 kilometers (24,901 miles), the automaker’s statement appears to be correct.

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Renault and Nissan partner with Waymo to develop self-driving services

The Renault-Nissan alliance has signed an exclusive deal with Google’s sister company Waymo to develop self-driving services in France and Japan.The tie-up between the car-makers and the autonomous vehicles company will focus on “all aspects” of driverless mobility services for moving people and goods.The deal does not currently extend to working together to build autonomous vehicles – unlike Waymo’s previous tie-ups with Jaguar Land Rover and Chrysler.

Waymo inks driverless car deal with Renault, Nissan to develop autonomous vehicles

Waymo unveils a self-driving Chrysler Pacifica minivan in Detroit, Michigan, U.S. on January 8, 2017.Brendan McDermid | Reuters Waymo has signed a deal with Renault and Nissan to develop self-driving cars and trucks for use in France, Japan and possibly other countries in Asia, including China, the autonomous car company announced Thursday.
It's the first agreement Waymo has signed to provide its technology and services to automakers working to build their own self-driving cars and services.
Waymo, a subsidiary of Google's parent company Alphabet, is currently testing a small fleet of autonomous vehicles just outside of Phoenix. Those vehicles, which are modified Chrysler Pacifica minivans, are part of Waymo's work to develop autonomous ride-share services. With Renault and Nissan, Waymo's relationship will be more as a provider of technology and services that each automaker will use as they develop their own self-driving vehicles.
“Our Waymo Driver can deliver transformational mobility solutions to safely serve riders and commercial deliveries in France, Japan and other countries,” John Krafcik, CEO of Waymo said in a prepared statement.
Renault and Nissan — which have a close yet strained relationship since the arrest and detention in October of Renault's former CEO Carlos Ghosn, who was also chairman of Nissan — are putting aside their differences when it comes to autonomous vehicles.
The companies said they're creating a joint venture companies to focus exclusively on driverless mobility services.
Thierry Bolloré, CEO of Renault, said in a statement that the deal will put his company, “at the forefront of driverless mobility new business streams in our key strategic markets.”
Hiroto Saikawa, president and CEO of Nissan echoed that confidence.
“Our expertise in the global automotive industry and expertise in strategic partnership will enable us to explore opportunities to grow our portfolio and deliver new value to customers with Waymo, the recognized leader in this space,” he said.
Waymo, formerly known as the Google Self Driving Car project, is considered a leader in autonomous vehicles, analysts and technology executives say.
That lead, however, is far from safe. General Motors' subsidiary Cruise, is expected to publicly launch its first autonomous vehicle later this year. Meanwhile, Uber is also working to develop autonomous ride-share vehicles.

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