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.
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Tesla finally brings a Robotaxi update that Android users will love
The breakdown of the software version shows that Tesla is actively developing an Android-compatible version of the Robotaxi app, and the company is developing Live Activities for Android.
Tesla is finally bringing an update of its Robotaxi platform that Android users will love — mostly because it seems like they will finally be able to use the ride-hailing platform that the company has had active since last June.
Based on a decompile of software version 26.2.0 of the Robotaxi app, Tesla looks to be ready to roll out access to Android users.
According to the breakdown, performed by Tesla App Updates, the company is preparing to roll out an Android version of the app as it is developing several features for that operating system.
🚨 It looks like Tesla is preparing to launch the Robotaxi app for Android users at last!
A decompile of v26.2.0 of the Robotaxi app shows some progress on the Android side for Robotaxi 🤖 🚗 https://t.co/mThmoYuVLy
— TESLARATI (@Teslarati) March 13, 2026
The breakdown of the software version shows that Tesla is actively developing an Android-compatible version of the Robotaxi app, and the company is developing Live Activities for Android:
“Strings like notification_channel_robotaxid_trip_name and android_native_alicorn_eta_text show exactly how Tesla plans to replicate the iOS Live Activities experience. Instead of standard push alerts, Android users are getting a persistent, dynamically updating notification channel.”
This is a big step forward for several reasons. From a face-value perspective, Tesla is finally ready to offer Robotaxi to Android users.
The company has routinely prioritized Apple releases because there is a higher concentration of iPhone users in its ownership base. Additionally, the development process for Apple is simply less laborious.
Tesla is working to increase Android capabilities in its vehicles
Secondly, the Robotaxi rollout has been a typical example of “slowly then all at once.”
Tesla initially released Robotaxi access to a handful of media members and influencers. Eventually, it was expanded to more users, so that anyone using an iOS device could download the app and hail a semi-autonomous ride in Austin or the Bay Area.
Opening up the user base to Android users may show that Tesla is preparing to allow even more users to utilize its Robotaxi platform, and although it seems to be a few months away from only offering fully autonomous rides to anyone with app access, the expansion of the user base to an entirely different user base definitely seems like its a step in the right direction.
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Lucid unveils Lunar Robotaxi in bid to challenge Tesla’s Cybercab in the autonomous ride hailing race
Lucid’s Lunar robotaxi is gunning for Tesla’s Cybercab in the autonomous ride hailing race
![Lucid Lunar robotaxi concept [Credit: Rendering by TESLARATI]](https://www.teslarati.com/wp-content/uploads/2026/03/lucid-lunar-robotaxi-concept-teslarati-rendering.jpg)
Lucid Group pulled back the curtain on its purpose-built autonomous robotaxi platform dubbed the Lunar Concept. Announced at its New York investor day event, Lunar is arguably the company’s most ambitious concept yet, and a direct line of sight toward the autonomous ride haling market that Tesla looks to control.
At Lucid Investor Day 2026, the company introduced Lunar, a purpose-built robotaxi concept based on the Midsize platform.
A comparison to Tesla’s Cybercab is unavoidable. The concept of a Tesla robotaxi was first introduced by Elon Musk back in April 2019 during an event dubbed “Autonomy Day,” where he envisioned a network of self-driving Tesla vehicles transporting passengers while not in use by their owners. That vision took another major step in October 2024 when, Musk unveiled the Cybercab at the Tesla “We, Robot” event held at Warner Bros. Studios in Burbank, California, where 20 concept Cybercabs autonomously drove around the studio lot giving rides to attendees.
Fast forward to today, and Tesla’s ambitions are finally materializing, but not without friction. As we recently reported, the Cybercab is being spotted with increasing frequency on public roads and across the grounds of Gigafactory Texas, suggesting that the company’s road testing and validation program is ramping meaningfully ahead of mass production. Tesla already operates a small scale robotaxi service in Austin using supervised Model Ys, but the Cybercab is designed from the ground up for high-volume, low-cost production, with Musk stating an eventual goal of producing one vehicle every 10 seconds.
At Lucid Investor Day 2026, the company introduced Lunar, a purpose-built robotaxi concept based on the Midsize platform.
Into this landscape steps Lucid’s Lunar. Built on the company’s all-new Midsize EV platform, which will also underpin consumer SUVs starting below $50,000. The Lunar mirrors the Cybercab’s core philosophy of having two seats, no driver controls, and a focus on fleet economics. The platform introduces Lucid’s redesigned Atlas electric drive unit, engineered to be smaller, lighter, and cheaper to manufacture at scale.
Unlike Tesla’s strategy of building its own ride hailing network from scratch, Lucid is partnering with Uber. The companies are said to be in advanced discussions to deploy Midsize platform vehicles at large scale, with Uber CEO Dara Khosrowshahi publicly backing Lucid’s engineering credentials and autonomous-ready architecture.
In the investor day event, Lucid also outlined a recurring software revenue model, with an in-vehicle AI assistant and monthly autonomous driving subscriptions priced between $69 and $199. This can be seen as a nod to the software revenue stream that Tesla has long championed with its Full Self-Driving subscription.
Tesla’s Cybercab is targeting a price point below $30k and with operating costs as low as 20 cents per mile. But with regulatory hurdles still ahead, the window for competition is open. Lucid’s Lunar may not have a launch date yet, but it arrives at a pivotal moment, and when the robotaxi race is no longer viewed as hypothetical. Rather, every serious EV player needs to come to bat on the same plate that Tesla has had countless practice swings on over the last seven years.
Elon Musk
Brazil Supreme Court orders Elon Musk and X investigation closed
The decision was issued by Supreme Court Justice Alexandre de Moraes following a recommendation from Brazil’s Prosecutor-General Paulo Gonet.
Brazil’s Supreme Federal Court has ordered the closure of an investigation involving Elon Musk and social media platform X. The inquiry had been pending for about two years and examined whether the platform was used to coordinate attacks against members of the judiciary.
The decision was issued by Supreme Court Justice Alexandre de Moraes following a recommendation from Brazil’s Prosecutor-General Paulo Gonet.
According to a report from Agencia Brasil, the investigation conducted by the Federal Police did not find evidence that X deliberately attempted to attack the judiciary or circumvent court orders.
Prosecutor-General Paulo Gonet concluded that the irregularities identified during the probe did not indicate fraudulent intent.
Justice Moraes accepted the prosecutor’s recommendation and ruled that the investigation should be closed. Under the ruling, the case will remain closed unless new evidence emerges.
The inquiry stemmed from concerns that content on X may have enabled online attacks against Supreme Court justices or violated rulings requiring the suspension of certain accounts under investigation.
Justice Moraes had previously taken several enforcement actions related to the platform during the broader dispute involving social media regulation in Brazil.
These included ordering a nationwide block of the platform, freezing Starlink accounts, and imposing fines on X totaling about $5.2 million. Authorities also froze financial assets linked to X and SpaceX through Starlink to collect unpaid penalties and seized roughly $3.3 million from the companies’ accounts.
Moraes also imposed daily fines of up to R$5 million, about $920,000, for alleged evasion of the X ban and established penalties of R$50,000 per day for VPN users who attempted to bypass the restriction.
Brazil remains an important market for X, with roughly 17 million users, making it one of the platform’s larger user bases globally.
The country is also a major market for Starlink, SpaceX’s satellite internet service, which has surpassed one million subscribers in Brazil.
Tesla finally brings a Robotaxi update that Android users will love
![Lucid Lunar robotaxi concept [Credit: Rendering by TESLARATI]](https://www.teslarati.com/wp-content/uploads/2026/03/lucid-lunar-robotaxi-concept-teslarati-rendering-80x80.jpg)
Lucid unveils Lunar Robotaxi in bid to challenge Tesla’s Cybercab in the autonomous ride hailing race
