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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. 

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. 

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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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Investor's Corner

Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet

Elon Musk says Starship Flight 15 will try to catch the ship itself, a first.

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Elon Musk says SpaceX’s next Starship flight will try something nobody has done before, by catching the ship itself. Speaking to roughly 2,000 people at the X Takeover event at Giga Texas on Saturday, Musk said Flight 15 is about four to six weeks away and “probably launches a little bit before Thanksgiving, is my guess.”

That is a slip from earlier reporting, which had pointed to a launch as early as October 19. Musk explained why the date keeps moving. “We’re making a bunch of improvements to the rocket between every flight,” he said, adding that there are often hundreds, sometimes thousands, of small changes. This time the list is short, “but some of them take a fair bit of work and we’ve got to go inside the tank to make some of these changes.”

“We’re going to try to catch the ship, which is a super big deal,” Musk said. “If we do so, that’ll be the first time that there’s been full recovery of an orbital class rocket.” SpaceX has already caught the Super Heavy booster with the tower’s mechanical arms, and has talked about catching the ship since late 2025, but the upper stage has never been caught.

Musk also laid out what comes after. “The next big milestone would be to refly both the booster and the ship,” he said, describing a Flight 16 where “all parts of an orbital rocket are reflown.”

The reason SpaceX wants this comes down to cost and cadence. Every Starship ship so far has ended its flight in the ocean, and SpaceX expects most of those water landings to end in fireballs. A ship that returns to Starbase intact can be inspected and flown again. SpaceX’s IPO filing, says Starship V3 is designed to deliver 100 metric tons to orbit in a fully reusable configuration, that SpaceX aims to cut the cost to reach orbit by 99% or more versus the historical average, and that tower catches should allow “multiple launches per day.”

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The payoff goes beyond cheaper launches. The next generation Starlink V3 satellites are too large for Falcon 9 and can only fly on Starship, which can carry up to 60 per flight. Flight 14 on September 28 deployed the first 26 of them after Starship reached orbit despite an early engine shutdown, as Teslarati reported. Musk blamed engine computer software, and said the heat shield “was extremely robust,” which he claimed in August had solved Starship’s biggest challenge.

NASA’s Moon plans depend on the same capability. NASA’s inspector general has described a lander mission that needs a propellant depot in low Earth orbit and more than 10 tanker flights, with SpaceX targeting one tanker launch every six days. That schedule only works if ships and boosters come back fast and fly again. Also, ship to ship propellant transfer has not been attempted yet.

One interesting hurdle yet to be explored is bringing the ship back to the launch site, with reentry over land, which will undoubtedly come with a lot of aviation safety reviews.

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Lifestyle

Tesla’s mirrorless Cybercab will give riders a visibility upgrade

Tesla engineer confirms Cybercab update letting riders pull up rear and repeater cameras on demand.

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Tesla Cybercab camera visibility for passengers (Credit: Dan Burkland via X)
Tesla Cybercab camera visibility for passengers (Credit: Dan Burkland via X)

Tesla is working on a Cybercab update that would let passengers pull up the vehicle’s rear and side cameras on demand, and the request came straight from a rider.

The exchange played out on X late Friday. Cybercab rider Dan Burkland shared photos of the two-seater’s cabin screen after an evening ride, praised the UI team’s work, and left one request: let riders open the rear and repeater cameras whenever they want, “especially for peace of mind.” Tesla UI software engineer Evan (@CarCoder) answered with two words: “In development.”

The idea fits a pattern Teslarati has tracked since public rides began. Days after paid Cybercab service opened in Austin, Tesla sent riders a survey that asked them to rate the touchscreen, the app and the cabin, and to pick the features they wanted most. We reported on that survey in September, and a camera view is the kind of small software change Tesla can push quickly if riders keep asking.

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It also speaks to something unique about the vehicle. With no steering wheel, no pedals and no driver, passengers have no mirror to check and no way to see behind them. The hardware is clearly built for camera awareness, from the repeater cameras to the rear camera. Letting a passenger look through those same cameras would give a nervous first time rider a way to confirm what is around the car.

The timing matters because the fleet is growing fast. Tesla’s Robotaxi account said on Saturday that more than 300 Cybercabs are now serving Austin, an eightfold increase in 30 days, and Tesla AI chief Ashok Elluswamy named Dallas as the next city. More cars and more cities mean more people riding in a driverless vehicle for the first time, which is exactly when small trust features carry weight.

For now, the feature is confirmed only as in development. If Tesla follows its usual pattern with Cybercab software, riders could see it appear in a point release without any announcement, and Teslarati will watch for it.

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News

Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next

Tesla confirms its first official Cybercab fleet number as Austin scales fast and Dallas looms.

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Tesla says more than 300 Cybercabs are now serving Austin, the first time the company has put an official number on its active Cybercab fleet. The figure came from the Robotaxi account on X on Saturday, which wrote that one month after launch the service had “scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days.”

Ashok Elluswamy, Tesla’s head of AI software, quoted the post with a line that carried the bigger news. “Two years since the 10/10 Cybercab WeRobot event, the cabs are everywhere in Austin now. Dallas soon,” he wrote. It is the first time Tesla has named the next city for public Cybercab rides.

Tesla opened Cybercab rides to the public in Austin on September 4, as Teslarati reported, a day after an invite only launch event. The ramp since then has been steep. Our September 28 report had the fleet at well over 100 units after availability jumped from 58 to 125 in a single week. On Thursday, Tesla added 150 Cybercabs to the Texas automated vehicle registry, lifting its registered count to 319 from 169. The first seven appeared on the registry on August 31.

RobotaxiTracker, a community site that counts vehicles from sightings and state records, listed 275 vehicles in unsupervised service in Austin on Saturday, 105 of them Cybercabs, which is well below Tesla’s figure. Tracker counts can lag official numbers, though Sawyer Merritt noted that Cybercab wait times in Austin stayed short on Saturday evening even with more than 2,000 fans in town for X Takeover.

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Regulators are watching the rollout. NHTSA opened an audit query into Tesla’s certification that the Cybercab meets federal safety standards, and sworn answers are due October 30. Tesla reports third quarter earnings on October 21, which gives the company a natural venue to define its fleet numbers and put a date on Dallas.

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