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.
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Elon Musk
Elon Musk reveals date of Tesla Full Self-Driving’s next massive release
Initially planned for a January or February release, v14.3 aims to add some reasoning and logic to the decisions that Full Self-Driving makes, which could improve a lot of things, including Navigation, which is a major complaint of many owners currently.
Tesla CEO Elon Musk revealed the date of Full Self-Driving’s next massive release: v14.3.
For months, Tesla owners with Hardware 4 have been utilizing Full Self-Driving v14.2 and subsequent releases. Currently, the most up-to-date FSD version is v14.2.2.5, which has definitely brought out mixed reviews. With releases, some things get better, and other things might regress slightly.
For the most part, things are better in terms of overall behavior.
However, many owners have been looking forward to the next release, which is v14.3, about which Musk has said many great things. Back in November, Musk said that v14.3 “is where the last big piece of the puzzle lands.”
He added:
“We’re gonna add a lot of reasoning and RL (reinforcement learning). To get to serious scale, Tesla will probably need to build a giant chip fab. To have a few hundred gigawatts of AI chips per year, I don’t see that capability coming online fast enough, so we will probably have to build a fab.”
Initially planned for a January or February release, v14.3 aims to add some reasoning and logic to the decisions that Full Self-Driving makes, which could improve a lot of things, including Navigation, which is a major complaint of many owners currently.
Tesla Full Self-Driving v14.2 is a considerable improvement from early versions of the suite, but we have written about the somewhat confusing updates that have come with recent versions.
Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
They’ve been incredibly difficult to gauge in terms of progress because some things have gotten better, but there seems to be some real regression on a handful of things, especially with confidence and assertiveness.
Musk confirmed today on X that Tesla is already testing v14.3 internally right now. It will hit a wide release “in a few weeks,” so we should probably expect it by late April.
It’s in testing right now. Wide release in a few weeks.
— Elon Musk (@elonmusk) March 19, 2026
Overall, there are high hopes that v14.3 could be a true game changer for Tesla Full Self-Driving, as many believe it could be the version that Robotaxis in Austin, Texas, some of which are driverless and unsupervised, are running.
It could also include some major additions, including “Banish,” also referred to as “Reverse Summon,” which would go find a parking spot after dropping occupants off at their destination.
What Tesla will roll out, and when exactly it arrives, all remain to be seen, but fans have been ready for a new version as v14.2.2.5 has definitely run its course. We have had a lot of readers tell us their biggest request is to fix Navigation errors, which seem to be one of the most universal complaints among daily FSD users.
Cybertruck
Chattanooga Charge: Tesla and EV fans ready for the Southeast’s wildest Tesla party
From Cybertruck Convoys to Kid-Friendly Fun Zones: The Chattanooga Charge Has Something for Everyone
Hundreds of like-minded Tesla and EV enthusiasts are descending on Chattanooga Charge this weekend for the largest Tesla meet in the Southeast. Taking place on March 20–22, 2026 at the stunning Tennessee Riverpark.
If you were there last year, you’ll know that it’s the ultimate experience to see the wildest Teslas in action, see the best in EV tech, and arguably the most fun – finally put a name to the face and connect with those social media buddies IRL! Oh, and that epic night time Tesla light show is a once-in-a-lifetime experience that will transform the Riverpark into something out of a sci-fi film that’s remarkably unforgettable and must be seen in person.
This year’s event takes everything up a notch, with over 100 Cybertrucks expected to be on display, many sporting jaw-dropping modifications and custom wraps that push the boundaries of what these stainless steel beasts can look like.
Whether you’re a diehard Tesla fan, EV supporter, or just EV-mod-curious, the sheer spectacle is worth the drive.
The Chattanooga Charge doesn’t wait until Saturday morning to get started. The weekend technically kicks off Friday, March 20th, and the venue sets the tone immediately. Come share roadtrip stories over drinks at the W-XYZ Rooftop Bar on the top floor of the Aloft Chattanooga Hamilton Place Hotel, with sunset views over the city.
Come morning, nurse your hangover with a some good coffee, and convoy with hundreds of other Tesla and EV drivers through Chattanooga to the event for some morning meet and greets before the speaker panel starts and the food trucks fire up.
Tesla owner clubs travel from across the country to be here, not just to show off their vehicles,, but to connect, share, and celebrate a shared passion for the future of driving.
Sounds like a plan to me. See you there, guys. Don’t miss it. Get your tickets at ChattanoogaCharge.com and join the charge. 🔋⚡
Chattanooga Charge is a premier Tesla and EV gathering inspired by the X Takeover, known as one of the largest Tesla event gatherings. What began as a bold idea from the team at DIY Wraps/TESBROS, hosted in their hometown of Chattanooga, Tennessee, the event quickly became a movement across social media. The first annual Chattanooga Charge united over 16 Tesla clubs from 16 states, proof that the EV community was hungry for something big in the South. Year after year, the event has grown in scale, ambition, and heart.
News
Tesla Full Self-Driving gets latest bit of scrutiny from NHTSA
The analysis impacts roughly 3.2 million vehicles across the company’s entire lineup, and aims to identify how the suite’s degradation detection systems work and how effective they are when the cars encounter difficult visibility conditions.
The National Highway Traffic Safety Administration (NHTSA) has elevated its probe into Tesla’s Full Self-Driving (Supervised) suite to an Engineering Analysis.
The analysis impacts roughly 3.2 million vehicles across the company’s entire lineup, and aims to identify how the suite’s degradation detection systems work and how effective they are when the cars encounter difficult visibility conditions.
The step up into an Engineering Analysis is often required before the NHTSA will tell an automaker to issue a recall. However, this is not a guarantee that a recall will be issued.
🚨 The NHTSA said it was upgrading a probe into Tesla’s Full Self-Driving (Supervised) platform to an “engineering analysis”
It will examine 3.2 million vehicles and aims to determine its effectiveness in evaluating degraded road conditions pic.twitter.com/2dkrv1mR8o
— TESLARATI (@Teslarati) March 19, 2026
The NTHSA wants to examine Tesla FSD’s ability to assess road conditions that have reduced visibility, as well as detect degradation to alert the driver with sufficient time to respond.
The Office of Defects Investigation (ODI) will evaluate the performance of FSD in degraded roadway conditions and the updates or modifications Tesla makes to the degradation detection system, including the timing, purpose, and capabilities of the updates.
Tesla routinely ships software updates to improve the capabilities of the FSD suite, so it will be interesting to see if various versions of FSD are tested. Interestingly, you can find many examples from real-world users of FSD handling snow-covered roads, heavy rain, and single-lane backroads.
However, there are incidents that the NHTSA has used to determine the need for this probe, at least for now. The agency said:
“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”
It continues to say in its report that a review of Tesla’s responses revealed additional crashes that occurred in similar environments showed FSD “did not detect a degraded state, and/or it did not present the driver with an alert with adequate time for the driver to react. In each of these crashes, FSD also lost track of or never detected a lead vehicle in its path.”
The next steps of the NHTSA Engineering Analysis require the agency to gather further information on Tesla’s attempts to upgrade the degradation detection system. It will also analyze six recent potentially related incidents.
The investigation is listed as EA26002.
Elon Musk reveals date of Tesla Full Self-Driving’s next massive release
Chattanooga Charge: Tesla and EV fans ready for the Southeast’s wildest Tesla party
