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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now. 

The following are Tesla’s FSD Beta V11.3 release notes

  • Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
  • Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
  • Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
  • Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
  • Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
  • Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
  • Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
  • Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
  • Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
  • Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
  • Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
  • Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines. 
  • Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
  • Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
  • Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
  • Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
  • Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
  • Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
  • Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.

Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver. 

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Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers. 

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

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 adjusts Robotaxi safety monitor strategy in Austin with new service area

The positioning of the driver, as well as the driver’s hands being closer to the steering wheel, is more similar to what Tesla is doing in the Bay Area Robotaxi program than it is to what it has done in Austin.

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Credit: @AdanGuajardo/X

Tesla has adjusted its Robotaxi safety monitor strategy in Austin after it expanded its service area in the city last week for the third time.

Tesla has been operating its Robotaxi platform in Austin since June 22. The vehicles have been operated without a driver, but Tesla has placed safety monitors in the passenger’s seat as a precaution.

The safety monitors are responsible for performing any necessary interventions and maintaining a safe and comfortable cabin for riders as they experience Tesla’s first venture into the driverless ride-sharing space.

Last week, Tesla expanded its service area in Austin for the third time, expanding it from about 90 square miles to 170 square miles. The expansion included new territory, including the Austin-Bergstrom International Airport, Tesla’s Gigafactory Texas, and several freeways.

Tesla Robotaxi geofence expansion enters Plaid Mode and includes a surprise

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The freeway is an area that is uncharted territory for the Tesla Robotaxi program, and this fact alone encouraged Tesla to switch up its safety monitor positioning for the time being.

For now, they will be riding in the driver’s seat when routes require freeway travel:

The positioning of the driver, as well as the driver’s hands being closer to the steering wheel, is more similar to what Tesla is doing in the Bay Area Robotaxi program than it is to what it has done in Austin.

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This is sure to draw criticism from skeptics, but it is simply a step to keep things controlled and safe while the first Robotaxi drives take passengers on the highway with this version of the Full Self-Driving software.

This FSD version differs from the one that customers have in their own vehicles, but CEO Elon Musk has indicated something big is coming soon. FSD v14 is coming to vehicles in the near future, and Musk has said its performance is pretty incredible.

Tesla’s Elon Musk shares optimistic teaser about FSD V14: “Feels sentient”

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Tesla has best month ever in Turkey with drastic spike in sales

Tesla managed to sell 8,730 Model Y vehicles in Turkey, outpacing almost every competitor by a substantial margin. Only one brand sold better than Tesla in August in Turkey, and it was Renault.

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Credit: Tesla

Tesla had its best monthly performance ever in Turkey in August, thanks to a drastic spike in sales.

Tesla saw an 86 percent bump in sales of the new Model Y in Turkey in August compared to July, dominating the market.

The performance was one of Tesla’s best in the market, and the company’s sales for the month accounted for half of all EV sales in Turkey for August, as it dominated and led BYD, which was the second-best-selling brand with just 1,639 units sold.

Tesla managed to sell 8,730 Model Y vehicles in Turkey, outpacing almost every competitor by a substantial margin. Only one brand sold better than Tesla in August in Turkey, and it was Renault.

Electric vehicles are, in some ways, more desirable than their gas counterparts in Turkey for several reasons. Most of the reasoning is financial.

First, EVs are subject to a lower Special Consumption Tax in Turkey. EVs can range from 25 percent to up to 170 percent, but this is less than the 70 to 220 percent rate that gas-powered vehicles can face. The tax is dependent on engine size.

Elon Musk courted to build a Tesla factory in Turkey

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Additionally, EVs are exempt from the annual Motor Vehicle Tax for the first ten years, providing consumers with a long-term ownership advantage. There are also credits that can amount to $30,000 in breaks, which makes them more accessible and brings down the cost of ownership.

Let’s not forget the other advantages that are felt regardless of country: cheaper fuel costs, reduced maintenance, and improved performance.

The base Model Y is the only configuration available in Turkey currently.

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Tesla is upgrading airbag safety through a crazy software update

“This upgrade builds upon your vehicle’s superior crash protection by now using Tesla Vision to help offer some of the most cutting-edge airbag performance in the event of a frontal crash.”

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(Credit: Tesla)

Tesla is upgrading airbag safety through a crazy software update, which will utilize the company’s vision-first approach to enable better protection in the event of an accident.

Over the years, Tesla has gained an incredible reputation for prioritizing safety in its vehicles, with crash test ratings at the forefront of its engineers’ minds.

This has led to Tesla gaining numerous five-star safety ratings and awards related to safety. It is not just a statistical thing, either. In the real world, we’ve seen Teslas demonstrate some impressive examples of crash safety.

Everything from that glass roof not caving in when a tree falls on it to a Model Y surviving a drive off a cliff has been recorded.

However, Tesla is always looking to improve safety, and unlike most companies, it does not need a physical hardware update to do so. It can enhance features such as crash response and airbag performance through Over-the-Air software updates, which download automatically to the vehicle.

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In Tesla’s 2025.32 Software Update, the company is rolling out a Frontal Airbag System Enhancement, which aims to use Tesla Vision, the company’s camera-based approach to self-driving, to keep occupants safe.

The release notes state (via NotaTeslaApp):

“This upgrade builds upon your vehicle’s superior crash protection by now using Tesla Vision to help offer some of the most cutting-edge airbag performance in the event of a frontal crash. Building on top of regulatory and industry crash testing, this release enables front airbags to begin to inflate and restrain occupants earlier, in a way that only Tesla’s integrated systems are capable of doing, making your car safer over time.”

The use of cameras to predict a better time to restrain occupants with seatbelts and inflate airbags prior to a collision is a fantastic way to prevent injuries and limit harm done to those in the vehicle.

The feature is currently limited to the Model Y.

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