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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Tesla expands Unsupervised Robotaxi service to two new cities
This expansion builds directly on Tesla’s existing operations. Robotaxi has been ramping unsupervised rides in Austin for months and maintains activity in the San Francisco Bay Area.
Tesla has taken a major step forward in its autonomous ride-hailing ambitions.
On April 18, the company’s official Robotaxi account announced that Robotaxi service is now rolling out in Dallas and Houston, Texas. The update signals the rapid scaling of unsupervised autonomous operations in the Lone Star State.
The announcement includes a compelling 14-second video captured from inside a Model Y. Shot from the passenger perspective, the footage shows the vehicle navigating suburban roads in both cities with zero driver intervention, with no Safety Monitor to be seen.
Robotaxi now rolling out in Dallas & Houston 🤠 pic.twitter.com/G3KFQwqGxB
— Tesla Robotaxi (@robotaxi) April 18, 2026
Tesla also shared geofence maps highlighting the initial service areas: a compact zone in Houston covering parts of Willowbrook and Jersey Village, and a similarly defined area in Dallas near Highland Park and central neighborhoods.
🚨 Tesla has expanded Robotaxi to two new cities: Houston and Dallas, joining Austin and the SF Bay Area as active Robotaxi areas https://t.co/S3Ck4EaGpR pic.twitter.com/N0qu0bcTyd
— TESLARATI (@Teslarati) April 18, 2026
This expansion builds directly on Tesla’s existing operations. Robotaxi has been ramping unsupervised rides in Austin for months and maintains activity in the San Francisco Bay Area.
With Dallas and Houston now live, Texas hosts three active hubs—an impressive concentration that triples the company’s Lone Star footprint in just weeks. The move aligns with Tesla’s Q4 2025 earnings guidance, which outlined a broader H1 2026 rollout across seven U.S. cities, including Phoenix, Miami, Orlando, Tampa, and Las Vegas.
Texas offers favorable regulations, high ride-share demand, and relatively straightforward suburban-to-urban driving patterns ideal for early autonomous scaling. While initial geofences appear modest—roughly 25 square miles per city—Tesla has historically expanded these zones quickly as it gathers real-world data.
Tesla confirms Robotaxi expansion plans with new cities and aggressive timeline
Unsupervised operation marks a critical milestone: passengers can summon, ride, and exit without safety drivers, a leap beyond many competitors still requiring human oversight.
For Tesla, the implications are significant. Successful scaling in major metros could accelerate the transition to a fully driverless fleet, unlocking new revenue streams and validating years of Full Self-Driving investment.
Riders gain convenient, potentially lower-cost mobility, while the company edges closer to Elon Musk’s vision of Robotaxis transforming urban transport.
As Tesla pushes into more cities this year, today’s launch in Dallas and Houston underscores its momentum. Hopefully, Tesla will be able to expand unsupervised rides to another U.S. state soon, which will mark yet another chapter in this short-but-encouraging Robotaxi story.
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Tesla is pushing Robotaxi features to owner cars with Spring Update
Tesla has quietly begun rolling out one of its most forward-looking Robotaxi-inspired features to existing customer vehicles.
Tesla is starting to push Robotaxi features to owner cars, and the first instances are coming as the Spring 2026 Update starts to roll out.
Tesla has quietly begun rolling out one of its most forward-looking Robotaxi-inspired features to existing customer vehicles.
With the 2026 Spring Update (version 2026.14+), the rear passenger display now features a fully interactive navigation map that works while the car is driving — a capability previously reserved for Tesla Robotaxi.
First look at Tesla’s v2026.14.1 Spring Update.
🧭Rear screen interactive map #teslaupdate #tesla #teslasrpingupdate pic.twitter.com/yH3T4U8qHp— Sergiu Mogan (@sergiumogan) April 17, 2026
Until now, Tesla’s rear displays have been largely limited to media controls, climate settings, and static route overviews. The new interactive map transforms the backseat into an active navigation hub, exactly the kind of passenger-first interface Tesla has been prototyping for its driverless fleet.
In a Robotaxi, where no one sits behind the wheel, every rider will need intuitive, real-time map access. By shipping this UI into thousands of owner cars months ahead of the Cybercab’s planned unveiling, Tesla is stress-testing the software in real-world conditions and giving loyal customers an early taste of the autonomous future.
The rollout is still in its early wave. Only a small number of vehicles have received 2026.14.1 so far, but the feature is expected to expand rapidly in the coming weeks. Owners of Model S, Model X, Model 3, Model Y, and Cybertruck are all eligible.
For buyers of the new Signature Edition Model S and X Plaid vehicles — whose deliveries begin in May — the update will likely arrive shortly after they take delivery, meaning the final chapter of Tesla’s flagship lineup will ship with cutting-edge Robotaxi preview tech baked in.
Elon Musk has long emphasized that Tesla ships supporting infrastructure well before new products launch. This rear-map rollout is a textbook example of that philosophy — quietly preparing both the software and the customer base for a world of fully driverless rides.
While the interactive map may seem like a modest convenience upgrade on the surface, its deeper purpose is unmistakable. Tesla is using its massive installed base of vehicles as a proving ground for the exact passenger experience that will define the Robotaxi era.
For current owners, it’s a free preview of tomorrow’s mobility; for the company, it’s invaluable data and real-world validation before the Cybercab hits the streets.
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Tesla Cybertruck sales bolstered by bold Musk move, report claims
If accurate, that means nearly one in every five Cybertrucks registered in the quarter was transferred internally within Musk’s business empire. The purchases, valued at more than $100 million, have continued into 2026.
A new report from Bloomberg claims Tesla Cybertruck sales were inflated by internal buyers, meaning companies owned by CEO Elon Musk, and most notably, SpaceX.
According to a new registration data analysis, a significant portion of the fourth quarter’s Cybertruck sales came from Musk companies.
In the fourth quarter of 2025, 7,071 Cybertrucks were registered in the United States. SpaceX, Musk’s rocket and satellite company, accounted for 1,279 of those vehicles—more than 18 percent of the total. Musk’s additional ventures, including xAI, the Boring Company, and Neuralink, acquired another 60 trucks during the same period.
Tesla Cybertruck just won a rare and elusive crash safety honor
If accurate, that means nearly one in every five Cybertrucks registered in the quarter was transferred internally within Musk’s business empire. The purchases, valued at more than $100 million, have continued into 2026.
These internal sales supplemented the Cybertruck’s overall performance for the quarter, as without them, sales would have plunged 51 percent. The vehicle, which has repeatedly been called “the best product Tesla has ever made,” has fallen short of expectations due to pricing.
When first unveiled back in 2019, Tesla had a $39,990, $49,990, and $69,990 configuration for sale. Those prices inflated significantly as the truck was not released to customers until 2023. Those who had placed orders for affordable configurations were priced out.
Sam Fiorani, VP of Global Vehicle Forecasting at AutoForecast Solutions, said, “Tesla is running out of buyers for the Cybertruck.” In reality, there are probably a lot of buyers, but they simply cannot afford the truck at its current price point.
The Cybertruck was supposed to broaden Tesla’s appeal beyond its core lineup of sleek sedans and SUVs. While it has done a lot for brand notoriety, it has not lived up to its monumental expectations, and it’s simply because the truck has not been as available as most had thought.
The truck is still the best-selling electric pickup in the country, outpacing rivals like the Ford F-150 Lightning and Chevrolet Silverado EV. It is also not uncommon for companies to use their own vehicles for internal operations, like Ford using its own Transit van for Mobile Service.
However, this much inventory of Cybertrucks being purchased by Musk’s companies is not what you love to see as a fan or investor.
Tesla expands Unsupervised Robotaxi service to two new cities
Tesla is pushing Robotaxi features to owner cars with Spring Update
