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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements.
Stay in your Lanes
- Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.
Nothing Like Smooth Driving
- Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
- Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
- Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
- Reduced latency when starting from a stop by accounting for lead vehicle jerk.
Chuck’s Left Turn
- Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.
Safety is Number 1
- Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
- Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Tesla FSD “Brain” Improvements
- Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
- Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
- Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
- Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
- Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
- Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
- Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.
Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.
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 adds awesome new driving feature to Model Y
Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.
Tesla is adding an awesome new driving feature to Model Y vehicles, effective on Juniper-updated models considered model year 2026 or newer.
Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.
Tesla writes in the release notes for the feature:
“Your Tesla now provides a smoother feel as you come to a complete stop during routine braking.”
🚨 Tesla has added a new “Comfort Braking” update with 2026.8
“Your Tesla provides a smoother feel as you come to a complete stop during routine braking.” https://t.co/afqCpBSVeA pic.twitter.com/C6MRmzfzls
— TESLARATI (@Teslarati) March 13, 2026
Interestingly, we’re not too sure what catalyzed Tesla to try to improve braking smoothness, because it hasn’t seemed overly abrupt or rough from my perspective. Although the brake pedal in my Model Y is rarely used due to Regenerative Braking, it seems Tesla wanted to try to make the ride comfort even smoother for owners.
There is always room for improvement, though, and it seems that there is a way to make braking smoother for passengers while the vehicle is coming to a stop.
This is far from the first time Tesla has attempted to improve its ride comfort through Over-the-Air updates, as it has rolled out updates to improve regenerative braking performance, handling while using Full Self-Driving, improvements to Steer-by-Wire to Cybertruck, and even recent releases that have combatted Active Road Noise.
Tesla holds a unique ability to change the functionality of its vehicles through software updates, which have come in handy for many things, including remedying certain recalls and shipping new features to the Full Self-Driving suite.
Tesla seems to have the most seamless OTA processes, as many automakers have the ability to ship improvements through a simple software update.
We’re really excited to test the update, so when we get an opportunity to try out Comfort Braking when it makes it to our Model Y.
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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.
News
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 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.