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 driverless Robotaxi geofence in Austin
Tesla has expanded the operational geofence for its driverless Robotaxi service in Austin, Texas, marking the first such increase in some time. The updated Service Area for Robotaxi in Austin now spans about 288 square miles and is roughly 9 percent larger than the previous boundary.
This incremental growth adds approximately 24 square miles of coverage, bringing the prior zone of roughly 264 square miles into a broader footprint that better serves northern suburbs.
The expansion extends the geofence northward toward Pflugerville along the US 183 corridor, incorporating additional neighborhoods north of the Domain and areas such as Mesa Park. These additions include higher-end residential and commercial districts that previously sat just outside the allowed operating zone.
Riders can now request unsupervised trips that begin or end in these newly included locations, provided the entire route remains inside the digital boundary:
Tesla has just expanded its Robotaxi service area in Austin, Texas for the first time in 10 months.
The new service area is roughly 9% larger than the old one, and is about 288 square miles in total. pic.twitter.com/i4oBM1KfWS
— Sawyer Merritt (@SawyerMerritt) August 31, 2026
Tesla first launched public Robotaxi operations in Austin in mid-2025 with a modest initial zone of about 20 square miles. Subsequent enlargements in 2025 and early 2026 steadily grew the map until it covered much of the metropolitan area.
After the last major update roughly ten months earlier, the company held the boundary steady while it collected additional miles and refined the FSD suite.
The modest nine percent increase still matters for daily utility. Longer trips become possible, more residents gain access, and the fleet can accumulate more diverse real-world data across new road types and traffic patterns. Observers note that the added territory aligns with existing Tesla service infrastructure, which could support more efficient vehicle staging in the North end of Austin.
Although the geofence has grown, Tesla continues to operate a relatively small unsupervised fleet in the city. The company has emphasized safety and software readiness over rapid geographic scaling. This latest map update signals that Tesla remains committed to expanding Robotaxi availability in its home market as it prepares for further software improvements and potential Cybercab deployments.
The 288-square-mile zone now gives Austin riders one of the larger driverless service areas currently available in the United States.
Elon Musk
Elon Musk’s Grok can basically control anything in your Tesla now
Tesla’s 2026 Summer Update turns Grok from a talking companion into a true in-car controller, with considerably expanded capabilities. Where the assistant once answered questions and handled navigation, it can now operate hardware and software through ordinary speech, including several requests at the same time.
Grok has become incredibly robust over the past few quarters, and this new ability that Tesla has included with its Summer Update is perhaps the clearest sign of just how capable it has become.
You can issue many commands to Grok at once, and each will be taken care of: anything from headlight control to climate adjustments to mirror folding can now all be taken care of with a simple sentence spoken toward Grok:
This is cool, you can now give Grok a ton of commands at once in your Tesla and it’ll do them all together.
The commands I gave:
• Fold mirrors
• Turn on wipers to fastest setting
• Change temp to 65°
• Open self-driving app
• Open gloveboxComes with Tesla’s 2026 Summer… pic.twitter.com/drZxoHrknv
— Sawyer Merritt (@SawyerMerritt) August 26, 2026
Here’s another example I used in my Model Y:
🚨 Using Grok to control the cabin temperature and turn on headlights in 2026 Model Y on FSD v14.3.8 and 2026.26.6.5 pic.twitter.com/7clgQkGABk
— TESLARATI (@Teslarati) August 27, 2026
Tesla’s official Release Notes list the core powers of Grok’s new capabilities: Grok can place phone calls from a paired phone, search a streaming service and queue music, adjust climate, and search the Controls panel. Drivers can also ask it questions about the vehicle or the latest features included in a recent software update.
It can also take care of driving settings, dynamics, and other relevant preferences that deal with how the car operates and handles.
Tesla Summer Update begins rolling out: a look at the new features
It’s also more of a use case than a novelty feature. Grok was great for learning about something that was being pondered while Full Self-Driving was taking care of the major automotive responsibilities, but it did have some useful functionality when it came to navigation.
Another less-noted improvement is the swift transition that Grok has from thinking of its answer to giving you one. In the past, it would take a few seconds for Grok to truly come up with a valuable response. It now seems that it is improving, at least slightly.
Elon Musk
Tesla is fixing Full Self-Driving’s pothole problem
Tesla Full Self-Driving is set to get a major fix with pothole avoidance, a feature that CEO Elon Musk said recently was “coming soon.” The feature has been included within the FSD v14 release notes for some time as an upcoming improvement.
Potholes come in all shapes and sizes, but one thing is universal about them, and that is the fact that every driver wants to avoid them. Driving into or over a pothole can cause tire and wheel damage, alignment issues, and even, in some more severe instances, injury to occupants or major damage to a vehicle in despair.
Tesla Cybercab uses a unique strategy for picking up the right rider
Musk said late last night in a post that pothole avoidance while utilizing the Full Self-Driving suite is “coming soon.”
Coming soon
— Elon Musk (@elonmusk) August 31, 2026
Full Self-Driving, even in its most recent and robust forms, still has its shortcomings. While the suite has performed exceptionally well with avoiding on-road obstacles like cardboard boxes, horse droppings, car parts, and other debris, it still seems to struggle with recognizing certain things.
Potholes and other abrupt changes in a road’s layout are things that FSD still tends to struggle with. Perhaps the suite’s 3D modeling is still in need of some additional data or some sort of script that will help it to avoid a potentially destructive pothole or bump in the road that would be easily recognizable by the human eye.
Musk has mentioned pothole avoidance for some time, with the initial idea coming in April 2019 when an owner first requested the feature. Musk said that Tesla would “definitely” develop pothole avoidance.
In August 2020, Musk said Tesla was in the process of labeling bumps and potholes so cars can either slow down or steer around them altogether.
Tesla to utilize micro maps for pothole-detection in future update
Avoiding major disturbances in the road is a necessary feature for Full Self-Driving to have, especially as Tesla is working toward a fully autonomous program that will eventually allow every occupant in the vehicle to sleep, work, or enjoy leisure time while traveling.
That truly begins this week with the launch of Cybercab on Thursday.