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Tesla Autopilot now enables the car to perceive space around it Tesla Autopilot now enables the car to perceive space around it

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Tesla Autopilot now enables the car to perceive space around it

Credit: Ashok Elluswamy

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Tesla Autopilot is now enabling the car to perceive the space around it thanks to the development of its Occupancy Networks. Tesla’s Autopilot Software Director, Ashok Elluswamy, shared a detailed thread on Twitter about a recent workshop the Autopilot team held. He also shared the workshop on Twitter.

In the video and Twitter Thread, Ashok explained how Tesla developed Occupancy Networks to literally give the car a sense of its surroundings. Humans have the ability to understand the objects around them at any given time. Is that car down the road moving at a slow speed or a fast speed? Do I, a pedestrian, have enough time to get across the street before being hit? What is that in the middle of the road? What is that falling from the sky? I should move out the way.

These reactions to scenarios and split-second decisions come naturally to humans. Tesla’s Autopilot Team is working to program the vehicles to do the same thing and this will save lives. Imagine the car being able to correctly detect its surroundings while the driver isn’t even paying attention. An example is sudden unintended accelerations (SUA). Ashok pointed out that Autopilot prevents around 40 of these types of accidents daily.

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The workshop was held in June at this year’s Conference on Computer Vision and Pattern Recognition (CVPR.) in New Orleans. Ashok explained that the team developed Occupancy Networks which enable the car to predict the volumetric occupancy of everything around it.

Ashok explained that the typical approaches such as image-space segmentation of free space or pixel-wise depth have many issues. The solution to those issues is Occupancy Networks.

In other words, Occupancy Networks enable the car to perceive the space around it and determine whether or not it can drive in that space. For example, if a UFO were to suddenly crash in front of you while you’re driving, you would react quickly in the safest way possible. This is what the Autopilot Team is training the software to do.

Ashok shared details of how Occupancy Networks used Neural Radience Fields (NeRFs). “The occupancy representation of these networks allows for differentiable rendering of images (based on the Neural Radiance Fields work). However, unlike typical NeRFs, which are per scene, these occupancy nets generalize across scenes.”

You can read Ashok’s full Twitter thread here and you can watch his presentation here. We are a little over a month before Tesla’s AI Day and I’m sure Tesla will share more about the life-saving technology it is working on as well as the Optimus Bot.

Dr. Know It All recently published a video about the new 10.69 update and shared his thought about Occupancy Network.

In a message on Twitter, he told me, “The beauty of Occupancy Networks is that the car doesn’t have to know what the objects it sees are, it just has to know that they are there in order to avoid them!”

Note: Johnna is a Tesla shareholder and supports its mission. 

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Your feedback is important. If you have any comments, concerns, or see a typo, you can email me at johnna@teslarati.com. You can also reach me on Twitter @JohnnaCrider1

Johnna Crider is a Baton Rouge writer covering Tesla, Elon Musk, EVs, and clean energy & supports Tesla's mission. Johnna also interviewed Elon Musk and you can listen here

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Tesla hints toward Premium Robotaxi offering with Model S testing

Why Tesla has chosen to use a couple of Model S units must have a reason; the company is calculated in its engineering and data collection efforts, so this is definitely more than “we just felt like giving our drivers a change of scenery.”

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Credit: Sawyer Merritt | X

Tesla Model S vehicles were spotted performing validation testing with LiDAR rigs in California today, a pretty big switch-up compared to what we are used to seeing on the roads.

Tesla utilizes the Model Y crossover for its Robotaxi fleet. It is adequately sized, the most popular vehicle in its lineup, and is suitable for a wide variety of applications. It provides enough luxury for a single rider, but enough room for several passengers, if needed.

However, the testing has seemingly expanded to one of Tesla’s premium flagship offerings, as the Model S was spotted with the validation equipment that is seen entirely with Model Y vehicles. We have written several articles on Robotaxi testing mules being spotted across the United States, but this is a first:

Why Tesla has chosen to use a couple of Model S units must have a reason; the company is calculated in its engineering and data collection efforts, so this is definitely more than “we just felt like giving our drivers a change of scenery.”

It seems to hint that Tesla could add a premium, more luxury offering to its Robotaxi platform eventually. Think about it: Uber has Uber Black, Lyft has Lyft Black. These vehicles and services are associated with a more premium cost as they combine luxury models with more catered transportation options.

Tesla could be testing the waters here, and it could be thinking of adding the Model S to its fleet of ride-hailing vehicles.

Reluctant to remove the Model S from its production plans completely despite its low volume contributions to the overall mission of transitioning the world to sustainable energy, the flagship sedan has always meant something. CEO Elon Musk referred to it, along with its sibling Model X, as continuing on production lines due to “sentimental reasons.”

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However, its purpose might have been expanded to justify keeping it around, and why not? It is a cozy, premium offering, and it would be great for those who want a little more luxury and are willing to pay a few extra dollars.

Of course, none of this is even close to confirmed. However, it is reasonable to speculate that the Model S could be a potential addition to the Robotaxi fleet. It’s capable of all the same things the Model Y is, but with more luxuriousness, and it could be the perfect addition to the futuristic fleet.

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Rivian unveils self-driving chip and autonomy plans to compete with Tesla

Rivian, a mainstay in the world of electric vehicle startups, said it plans to roll out an Autonomy+ subscription and one-time purchase program, priced at $49.99 per month and $2,500 up front, respectively, for access to its self-driving suite.

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Credit: Rivian

Rivian unveiled its self-driving chip and autonomy plans to compete with Tesla and others at its AI and Autonomy Day on Thursday in Palo Alto, California.

Rivian, a mainstay in the world of electric vehicle startups, said it plans to roll out an Autonomy+ subscription and one-time purchase program, priced at $49.99 per month and $2,500 up front, respectively, for access to its self-driving suite.

CEO RJ Scaringe said it will learn and become more confident and robust as more miles are driven and it gathers more data. This is what Tesla uses through a neural network, as it uses deep learning to improve with every mile traveled.

He said:

“I couldn’t be more excited for the work our teams are driving in autonomy and AI. Our updated hardware platform, which includes our in-house 1600 sparse TOPS inference chip, will enable us to achieve dramatic progress in self-driving to ultimately deliver on our goal of delivering L4. This represents an inflection point for the ownership experience – ultimately being able to give customers their time back when in the car.”

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At first, Rivian plans to offer the service to personally-owned vehicles, and not operate as a ride-hailing service. However, ride-sharing is in the plans for the future, he said:

“While our initial focus will be on personally owned vehicles, which today represent a vast majority of the miles to the United States, this also enables us to pursue opportunities in the rideshare space.”

The Hardware

Rivian is not using a vision-only approach as Tesla does, and instead will rely on 11 cameras, five radar sensors, and a single LiDAR that will face forward.

It is also developing a chip in-house, which will be manufactured by TSMC, a supplier of Tesla’s as well. The chip will be known as RAP1 and will be about 50 times as powerful as the chip that is currently in Rivian vehicles. It will also do more than 800 trillion calculations every second.

RAP1 powers the Autonomy Compute Module 3, known as ACM3, which is Rivian’s third-generation autonomy computer.

ACM3 specs include:

  • 1600 sparse INT8 TOPS (Trillion Operations Per Second).
  • The processing power of 5 billion pixels per second.
  • RAP1 features RivLink, a low-latency interconnect technology allowing chips to be connected to multiply processing power, making it inherently extensible.
  • RAP1 is enabled by an in-house developed AI compiler and platform software

As far as LiDAR, Rivian plans to use it in forthcoming R2 cars to enable SAE Level 4 automated driving, which would allow people to sit in the back and, according to the agency’s ratings, “will not require you to take over driving.”

More Details

Rivian said it will also roll out advancements to the second-generation R1 vehicles in the near term with the addition of UHF, or Universal Hands-Free, which will be available on over 3.5 million miles of roadway in the U.S. and Canada.

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Rivian will now join the competitive ranks with Tesla, Waymo, Zoox, and others, who are all in the race for autonomy.

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Tesla partners with Lemonade for new insurance program

Tesla recently was offered “almost free” coverage for Full Self-Driving by Lemonade’s Shai Wininger, President and Co-founder, who said it would be “happy to explore insuring Tesla FSD miles for (almost) free.”

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Credit: Tesla

Tesla owners in California, Oregon, and Arizona can now use Lemonade Insurance, the firm that recently said it could cover Full Self-Driving miles for “almost free.”

Lemonade, which offered the new service through its app, has three distinct advantages, it says:

  • Direct Connection for no telematics device needed
  • Better customer service
  • Smarter pricing

The company is known for offering unique, fee-based insurance rates through AI, and instead of keeping unclaimed premiums, it offers coverage through a flat free upfront. The leftover funds are donated to charities by its policyholders.

On Thursday, it announced that cars in three states would be able to be connected directly to the car through its smartphone app, enabling easier access to insurance factors through telematics:

Tesla recently was offered “almost free” coverage for Full Self-Driving by Lemonade’s Shai Wininger, President and Co-founder, who said it would be “happy to explore insuring Tesla FSD miles for (almost) free.”

The strategy would be one of the most unique, as it would provide Tesla drivers with stable, accurate, and consistent insurance rates, while also incentivizing owners to utilize Full Self-Driving for their travel miles.

Tesla Full Self-Driving gets an offer to be insured for ‘almost free’

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This would make FSD more cost-effective for owners and contribute to the company’s data collection efforts.

Data also backs Tesla Full Self-Driving’s advantages as a safety net for drivers. Recent figures indicate it was nine times less likely to be in an accident compared to the national average, registering an accident every 6.36 million miles. The NHTSA says a crash occurs approximately every 702,000 miles.

Tesla also offers its own in-house insurance program, which is currently offered in twelve states so far. The company is attempting to enter more areas of the U.S., with recent filings indicating the company wants to enter Florida and offer insurance to drivers in that state.

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