Tesla appears to have started slowly rolling out v11 of the Full Self-Driving Beta program this morning, just a few days after CEO Elon Musk stated the company would begin releasing it to more vehicles.
Tesla’s FSD Beta v11.3.1 started to roll out to employees late last year and a select few of the automaker’s long-standing testers a few weeks ago.
The controlled rollout allows Tesla to monitor its behaviors and tendencies in a highly safe way, as it can determine issues or bugs in a small sample size and fix them before a wider release begins.
On March 14, Musk stated that “ V11 starts going wide this weekend,” and we’ve heard it before. However, it appears the automaker is happy with the early reviews and is starting to release it to more vehicles.
V11 starts going wide this weekend
— Elon Musk (@elonmusk) March 15, 2023
v11.3.2 is the newest version of the Beta and is being rolled out with Tesla Software Update 2022.45.11. According to statistics from TeslaScope, more vehicles are being updated with the new FSD Beta v11, and more drivers on the r/TeslaMotors subreddit are beginning to report that they have received the update.
Drivers who have experienced the early editions of this rollout have reported that there have been several improvements to highway driving, and inner-city street navigation has also been refined and feels more accurate than ever before, which is undoubtedly a step in the right direction.
The full release notes for the FSD Beta are available below via TeslaScope:
- 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.
- Improved recall for close-by cut-in cases by 15%, particularly for large trucks and high-yaw rate scenarios, through an additional 30k auto-labeled clips mined from the fleet. Additionally, expanded and tuned dedicated speed control for cut-in objects.
- Improved the position of ego in wide lanes, by biasing in the direction of the upcoming turn to allow other cars to maneuver around ego.
- Improved handling during scenarios with high curvature or large trucks by offsetting in lane to maintain safe distances to other vehicles on the road and increase comfort.
- Improved behavior for path blockage lane changes in dense traffic. Ego will now maintain more headway in blocked lanes to hedge for possible gaps in dense traffic.
- Improved lane changes in dense traffic scenarios by allowing higher acceleration during the alignment phase. This results in more natural gap selection to overtake adjacent lane vehicles very close to ego.
- Made turns smoother by improving the detection consistency between lanes, lines and road edge predictions. This was accomplished by integrating the latest version of the lane-guidance module into the road edge and lines network.
- Improved accuracy for detecting other vehicles’ moving semantics. Improved precision by 23% for cases where other vehicles transition to driving and reduced error by 12% for cases where Autopilot incorrectly detects its lead vehicle as parked. These were achieved by increasing video context in the network, adding more data of these scenarios, and increasing the loss penalty for control- relevant vehicles.
- Extended maximum trajectory optimization horizon, resulting in smoother control for high curvature roads and far away vehicles when driving at highway speeds.
- Improved driving behavior next to row of parked cars in narrow lanes, preferring to offset and staying within lane instead of unnecessarily lane changing away or slowing down.
- Improved back-to-back lane change maneuvers through better fusion between vision-based localization and coarse map lane counts.
- Added text blurbs in the user interface to communicate upcoming maneuvers that FSD Beta plans to make. Also improved the visualization of upcoming slowdowns along the vehicle’s path. Chevrons render at varying opacity and speed to indicate the slowdown intensity, and a solid line appears at locations where the car will come to a stop.
- Improved the recall and precision of object detection, notably reducing the position error of semi-trucks by 10%, increasing the recall and precision of crossing vehicles over 100m away by 3% and 7%, respectively, and increasing the recall of motorbikes by 5%. This was accomplished by implementing additional quality checks in our two million video clip autolabeled dataset.
- Reduced false offsetting around objects in wide lanes and near intersections by improving object kinematics modeling in low speed scenarios.
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Elon Musk
Tesla Full Self-Driving’s newest behavior is the perfect answer to aggressive cars
According to a recent video, it now appears the suite will automatically pull over if there is a tailgater on your bumper, the most ideal solution for when a driver is riding your bumper.
Tesla Full Self-Driving appears to have a new behavior that is the perfect answer to aggressive drivers.
According to a recent video, it now appears the suite will automatically pull over if there is a tailgater on your bumper, the most ideal solution for when a driver is riding your bumper.
With FSD’s constantly-changing Speed Profiles, it seems as if this solution could help eliminate the need to tinker with driving modes from the person in the driver’s seat. This tends to be one of my biggest complaints from FSD at times.
A video posted on X shows a Tesla on Full Self-Driving pulling over to the shoulder on windy, wet roads after another car seemed to be following it quite aggressively. The car looks to have automatically sensed that the vehicle behind it was in a bit of a hurry, so FSD determined that pulling over and letting it by was the best idea:
Tesla appears to be implementing some sort of feature that will now pull over if someone is tailgating you to let the car by
Really cool feature, definitely get a lot of this from those who think they drive race cars
— TESLARATI (@Teslarati) February 26, 2026
We can see from the clip that there was no human intervention to pull over to the side, as the driver’s hands are stationary and never interfere with the turn signal stalk.
This can be used to override some of the decisions FSD makes, and is a great way to get things back on track if the semi-autonomous functionality tries to do something that is either unneeded or not included in the routing on the in-car Nav.
FSD tends to move over for faster traffic on the interstate when there are multiple lanes. On two-lane highways, it will pass slower cars using the left lane. When faster traffic is behind a Tesla on FSD, the vehicle will move back over to the right lane, the correct behavior in a scenario like this.
Perhaps one of my biggest complaints at times with Full Self-Driving, especially from version to version, is how much tinkering Tesla does with Speed Profiles. One minute, they’re suitable for driving on local roads, the next, they’re either too fast or too slow.
When they are too slow, most of us just shift up into a faster setting, but at times, even that’s not enough, see below:
What has happened to Mad Max?
At one point it was going 32 in a 35. Traffic ahead had pulled away considerably https://t.co/bjKvaMVTNX pic.twitter.com/aaZSWmLu5v
— TESLARATI (@Teslarati) January 24, 2026
There are times when it feels like it would be suitable for the car to just pull over and let the vehicle that is traveling behind pass. This, at least up until this point, it appears, was something that required human intervention.
Now, it looks like Tesla is trying to get FSD to a point where it just knows that it should probably get out of the way.
Elon Musk
Tesla Megapack powers $1.1B AI data center project in Brazil
By integrating Tesla’s Megapack systems, the facility will function not only as a major power consumer but also as a grid-supporting asset.
Tesla’s Megapack battery systems will be deployed as part of a 400MW AI data center campus in Uberlândia, Brazil. The initiative is described as one of Latin America’s largest AI infrastructure projects.
The project is being led by RT-One, which confirmed that the facility will integrate Tesla Megapack battery energy storage systems (BESS) as part of a broader industrial alliance that includes Hitachi Energy, Siemens, ABB, HIMOINSA, and Schneider Electric. The project is backed by more than R$6 billion (approximately $1.1 billion) in private capital.
According to RT-One, the data center is designed to operate on 100% renewable energy while also reinforcing regional grid stability.
“Brazil generates abundant energy, particularly from renewable sources such as solar and wind. However, high renewable penetration can create grid stability challenges,” RT-One President Fernando Palamone noted in a post on LinkedIn. “Managing this imbalance is one of the country’s growing infrastructure priorities.”
By integrating Tesla’s Megapack systems, the facility will function not only as a major power consumer but also as a grid-supporting asset.
“The facility will be capable of absorbing excess electricity when supply is high and providing stabilization services when the grid requires additional support. This approach enhances resilience, improves reliability, and contributes to a more efficient use of renewable generation,” Palamone added.
The model mirrors approaches used in energy-intensive regions such as California and Texas, where large battery systems help manage fluctuations tied to renewable energy generation.
The RT-One President recently visited Tesla’s Megafactory in Lathrop, California, where Megapacks are produced, as part of establishing the partnership. He thanked the Tesla team, including Marcel Dall Pai, Nicholas Reale, and Sean Jones, for supporting the collaboration in his LinkedIn post.
Elon Musk
Starlink powers Europe’s first satellite-to-phone service with O2 partnership
The service initially supports text messaging along with apps such as WhatsApp, Facebook Messenger, Google Maps and weather tools.
Starlink is now powering Europe’s first commercial satellite-to-smartphone service, as Virgin Media O2 launches a space-based mobile data offering across the UK.
The new O2 Satellite service uses Starlink’s low-Earth orbit network to connect regular smartphones in areas without terrestrial coverage, expanding O2’s reach from 89% to 95% of Britain’s landmass.
Under the rollout, compatible Samsung devices automatically connect to Starlink satellites when users move beyond traditional mobile coverage, according to Reuters.
The service initially supports text messaging along with apps such as WhatsApp, Facebook Messenger, Google Maps and weather tools. O2 is pricing the add-on at £3 per month.
By leveraging Starlink’s satellite infrastructure, O2 can deliver connectivity in remote and rural regions without building additional ground towers. The move represents another step in Starlink’s push beyond fixed broadband and into direct-to-device mobile services.
Virgin Media O2 chief executive Lutz Schuler shared his thoughts about the Starlink partnership. “By launching O2 Satellite, we’ve become the first operator in Europe to launch a space-based mobile data service that, overnight, has brought new mobile coverage to an area around two-thirds the size of Wales for the first time,” he said.
Satellite-based mobile connectivity is gaining traction globally. In the U.S., T-Mobile has launched a similar satellite-to-cell offering. Meanwhile, Vodafone has conducted satellite video call tests through its partnership with AST SpaceMobile last year.
For Starlink, the O2 agreement highlights how its network is increasingly being integrated into national telecom systems, enabling standard smartphones to connect directly to satellites without specialized hardware.
Tesla Full Self-Driving’s newest behavior is the perfect answer to aggressive cars
Tesla Megapack powers $1.1B AI data center project in Brazil
