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Tesla FSD Beta 10.11 release notes tease critical improvements

Credit: @evamcmillan333/Twitter)

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The release notes for Tesla’s Full Self-Driving Beta v10.11 hint at a number of critical improvements for the advanced driver-assist software. Tesla FSD Beta 10.11 is rolling out to Tesla employees for the time being. However, if the system performs well, external users should receive the update within the coming days. 

There are several notable improvements outlined in FSD Beta v10.11’s release notes. Tesla stated that V10.11 utilizes more accurate predictions of where other vehicles are turning or merging, reducing unnecessary slowdowns. The company also stated that V10.11 should improve vehicles’ right-of-way understanding, which should be invaluable in scenarios when maps turn out to be inaccurate.

More importantly, FSD Beta V10.11 featured specific improvements for vulnerable road users (VRU). Tesla notes that the most recent version of FSD Beta should improve VRU detection by 44.9%, allowing the system to dramatically reduce “spurious false positive pedestrians and bicycles.” The company was able to accomplish these VRU improvements by increasing the size of its next-generation labelers. 

Following are FSD Beta v10.11’s release notes

Early Access Program | FSD Beta 10.11 

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– Upgraded modeling of lane geometry from dense rasters (“bag of points”) to an autoregressive decoder that directly predicts and connects “vector space” lanes point by point using a transformer neural network. This enables us to predict crossing lanes, allows computationally cheaper and less error-prone post-processing, and paves the way for predicting many other signals and their relationships jointly and end-to-end. 

– Use more accurate predictions of where vehicles are turning or merging to reduce unnecessary slowdowns for vehicles that will not cross our path. 

– Improved right-of-way understanding if the map is inaccurate or the car cannot follow the navigation. In particular, modeling intersection extents is now entirely based on network predictions and no longer uses map-based heuristics. 

– Improved the precision of VRU detections by 44.9%, dramatically reducing spurious false positive pedestrians and bicycles (especially around tar seams, skid marks, and rain drops). This was accomplished by increasing the data size of the next-gen auto-labeler, training network parameters that were previously frozen, and modifying the network loss functions. We find that this decreases the incidence of VRU-related false slowdowns. 

– Reduced the predicted velocity error of very close-by motorcycles, scooters, wheelchairs, and pedestrians by 63.6%. To do this, we introduced a new dataset of simulated adversarial high-speed VRU interactions. This update improves autopilot control around fast-moving and cutting-in VRUs. 

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– Improved creeping profile with higher jerk when creeping starts. 

– Improved control for nearby obstacles by predicting continuous distance to static geometry with the general static obstacle network. 

– Reduced vehicle “parked” attribute error rate by 17%, achieved by increasing the dataset size by 14%. 

– Improved clear-to-go scenario velocity error by 5% and highway scenario velocity error by 10%, achieved by tuning loss function targeted at improving performance in difficult scenarios. 

– Improved detection and control for open car doors. 

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– Improved smoothness through turns by using an optimization-based approach to decide which road lines are irrelevant for control given lateral and longitudinal acceleration and jerk limits as well as vehicle kinematics. 

– Improved stability of the FSD Ul visualizations by optimizing the ethernet data transfer pipeline by 15%.

Tesla FSD Beta v10.11 will likely be released as software version number 2022.4.5.15, as per reports from the online electric vehicle community. Tests of v10.11’s performance in real-world roads are typically shared by members of the company’s FSD Beta program within hours of the system’s wide release. 

The Teslarati team would appreciate hearing from you. If you have any tips, reach out to me at maria@teslarati.com or via Twitter @Writer_01001101.

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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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.”

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.”

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.

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’

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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