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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 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
