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.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
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.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
News
Tesla plans ingenious improvement to one of its best features
Tesla is planning to improve one of the best features on its lineup of cars, a new patent shows. Tesla’s massive glass roof on its premium models is among the coolest additions to the all-electric vehicles, but the design certainly has its complaints, especially from those who live in even slightly warm climates.
Tesla has published a new patent that promises to transform cabin comfort in its electric vehicles, particularly those equipped with the expansive glass roofs.
The document, identified as US20260091643A1 and titled “Airflow Optimization for Cabin Comfort“, addresses that common complaint. Sunlight streaming through windshields and panoramic roofs creates localized hot air pockets near the dashboard and headliner. These pockets generate significant temperature gradients that conventional heating, ventilation, and air conditioning systems struggle to manage evenly.
The exposure to direct sunlight can make the cabin extremely warm, and even after cooling down the interior temperature, combating the continuous stream of sunlight and heat is a challenge. It uses precious energy that is especially pertinent to range and efficiency.
The patent explains how standard dashboard vents push cool air upward, only to entrain warmer air from these stagnant zones and distribute it throughout the occupied cabin space. This process forces the blower to operate at higher speeds, increasing energy consumption and reducing overall efficiency.
In electric vehicles, where every watt impacts driving range, such inefficiencies prove costly.
🚨 THE MODEL Y L IS THE MOST WATCHED EV LAUNCH OF 2026. ITS GLASS ROOF HAS ONE WEAKNESS — AND A PATENT PUBLISHED THIS WEEK SHOWS @TESLA BUILT THE FIX
The Model Y L launched in China and is now arriving in Korea, Japan, and across Asia-Pacific. It also has a glass roof. So does… https://t.co/wr6XnBn1Oc pic.twitter.com/5sYpniXJbU
— SETI Park (@seti_park) April 5, 2026
Research from AAA indicates that air conditioning can diminish range by up to 17 percent under hot conditions. Tesla’s innovation shifts the approach by extracting heat at its source rather than attempting to dilute it after mixing occurs.
Engineers describe a suction HVAC unit connected to dedicated intakes positioned strategically on the upper dashboard surface and within the headliner.
These intakes link to a hot air pocket extraction duct that channels the warmest air directly into the system’s plenum for conditioning. As the blower activates, it simultaneously draws recirculated cabin air and targeted hot pocket air through filters and cooling coils before redistributing conditioned airflow.
It seems somewhat reminiscent of the Tesla heat pump, which aims to combat colder temperatures.
Tesla highlights Model Y’s heat pump innovations in new promotional video
This method reduces entrainment, lowers peak temperatures, and achieves more uniform comfort levels. Testing data reveals that facial temperature gradients drop from 21 degrees Celsius, or 69.8 degrees Fahrenheit, in conventional setups to just 12 degrees Celsius (53.6 degrees F) with the new system. Blower speeds and compressor power requirements decrease appreciably as a result.
The design incorporates smart controls that monitor sunlight intensity and internal temperature distributions in real time. Suction activates selectively only where needed, optimizing energy use without constant high demand. Furthermore, the extraction duct serves a dual purpose.
In the summer months, it pulls hot air inward for cooling; in winter, it reverses to direct warm air outward for rapid windshield defrosting. This versatility allows the reuse of existing hardware with minimal modifications, potentially enabling retrofits in current Tesla fleets.
Lifestyle
Tesla saves its passengers again – This time after a 300-foot cliff fall in Malibu
A Tesla Model 3 fell 300 feet off a Malibu cliff and both passengers survived.
A Tesla Model 3 plunged roughly 300 feet off a cliff on Mulholland Highway in Malibu on Friday morning, May 29, 2026, and both occupants survived. The crash was reported at approximately 7:30 a.m. near the 2500 block of Mulholland Highway, triggering a multi-agency rescue operation involving Malibu Search and Rescue, the Los Angeles County Fire Department, the California Highway Patrol, and McCormick Ambulance.
When first responders arrived, the male driver was outside the vehicle shouting for help while the female passenger remained pinned inside the Tesla. Rescue crews rappelled down the cliffside on ropes to reach the wreckage. A flight medic was lowered by helicopter to begin treating both victims, and the driver was hoisted up to the roadway before crews used the Jaws of Life to free the trapped passenger. Both were airlifted to a local trauma center with moderate injuries despite a remarkable result for a fall that steep.
The outcome is not surprising, considering Model 3 earned an overall 5-star rating from NHTSA in every category and sub-category, and recorded the lowest probability of injury of any car ever evaluated by the U.S. New Car Assessment Program. The absence of a traditional engine in the front of the vehicle creates a longer crumple zone that absorbs impact energy before it reaches occupants, and the battery pack running along the floor gives the car an unusually low center of gravity that reinforces structural rigidity.
This is not the first time a Tesla has kept passengers alive after going off a cliff. A Tesla Model Y carrying a family of four survived a plunge off a cliff at Devil’s Slide near San Francisco in January 2023, with two adults and two children walking away from a 250-foot fall. That incident drew widespread attention to how the structural integrity of Tesla’s electric platform performs in extreme crash scenarios that most vehicles would not survive.
Tesla Model Y driver who drove off cliff with family attempts to avoid criminal conviction
News
Tesla Full Self-Driving expansion in Europe continues with new addition
Tesla Full Self-Driving (Supervised) has taken yet another significant step forward in Europe. On May 29, Estonia became the third European Union country to approve the advanced driver-assistance technology, following approvals in the Netherlands and Lithuania.
Tesla Europe announced the news on X, confirming the expansion has continued across the continent that, at one time, seemed to be taking its sweet old time giving any approval to the FSD suite.
FSD Supervised now approved in Estonia🇪🇪. Rollout will begin soon pic.twitter.com/y5a64qlp5m
— Tesla Europe, Middle East & Africa (@teslaeurope) May 29, 2026
Estonia’s Transport Administration (Transpordiamet) granted the approval by recognizing the type certification issued by the Dutch vehicle authority RDW. This mutual recognition mechanism, enabled by EU regulations, allows other member states to fast-track deployment without repeating extensive local testing.
The Estonian authority noted that Tesla’s FSD had undergone rigorous evaluation on European roads for approximately 18 months before the initial Dutch approval in April 2026.
FSD Supervised remains classified as a Level 2 advanced driver-assistance system (ADAS). Drivers must maintain full attention, keep their hands on the wheel, and stay ready to intervene at any moment.
The system assists with tasks such as automatic lane changes, navigation through city streets, and responding to traffic objects, but it does not constitute full autonomy. Estonian officials emphasized this distinction, underscoring that safety responsibility lies entirely with the driver.
The rapid progression across the Baltic region highlights Tesla’s strategic approach to European expansion. The Netherlands provided the foundational type approval in April, unlocking doors for neighboring countries.
Lithuania followed swiftly in mid-May, with rollout beginning shortly thereafter. Estonia’s decision, coming just days later, demonstrates how smaller, digitally progressive nations are accelerating adoption.
Tesla owners in Estonia can expect an over-the-air software update in the coming weeks, bringing the latest FSD capabilities to compatible vehicles
This expansion builds on Tesla’s global momentum. FSD Supervised is now available in 11 countries worldwide, including the United States, Canada, Australia, and South Korea. In Europe, the approvals signal growing regulatory confidence in Tesla’s vision-based AI approach, which relies on cameras and neural networks rather than lidar or radar-heavy alternatives used by some competitors.
For Tesla, these European milestones are more than symbolic. They validate years of data collection and software iteration while opening new revenue streams through FSD subscriptions and purchases.
As the company continues refining its AI models with real-world miles from diverse driving environments, including Estonia’s variable winter conditions, the dataset grows richer, potentially benefiting global users.