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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving

(Credit: Tesla)

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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.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla Roadster event gets delayed due to unfavorable weather

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Credit: Tesla

Tesla is delaying its event for the Roadster, moving it from this Thursday, October 1, to Thursday, October 15, due to unfavorable weather.

The company has said it has been tracking the weather for this Thursday closely with local meteorologists, and because the event can only be held outside, Tesla is making the call to delay it:

“We’ve been tracking the weather closely with local meteorologists, but given the severe conditions predicted & because this event can only be held outdoors, we’ve made the difficult decision to reschedule. New date is October 15. Additional details to follow.”

We are sure that this is bringing back PTSD for some Tesla fans, and we know it is not ideal, but this also reveals some things about the event. Tesla said that this can only be held outdoors, meaning it bodes well for the rumors that the vehicle could potentially hover.

Some believe that this was essentially confirmed by the FAA airspace restriction they were granted, but this could have been for a drone show or to keep drones from spying on the event.

Tesla Roadster is available for order once again following brief hold

The Roadster event has been long-awaited, and it is unfortunate that the weather is going to keep us all waiting a little bit longer.

The Tesla Roadster will be unveiled in Waco, Texas.

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SpaceX turned a heralding moment for Starship into its greatest

Starship reached orbit despite losing an engine, deployed 26 Starlink V3 satellites on Flight 14.

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SpaceX’s Starship reached orbit for the first time on Monday, and for a few nail-biting minutes it looked like it wouldn’t. During ascent on Flight 14, one of Ship 41’s six Raptor engines shut down early, and SpaceX’s livestream host Dan Huot told viewers the team had decided not to commit to orbit. Minutes later, after what Huot described as a lot of conversation in the control room, the final poll came back in favor, and a roughly 19 second burn of a single Raptor pushed the ship into orbit about 170 miles up.

The reversal matters because SpaceX had written the exit ramp into the mission plan. The company said it would only fire the orbital insertion burn if flight controllers confirmed enough backup hardware remained for the deorbit burn, a condition Teslarati laid out ahead of the flight. Losing an engine was exactly the scenario that rule was built for.

Pressing forward fits Elon Musk’s history. Falcon 1 failed three straight times before its fourth launch reached orbit in 2008, with SpaceX nearly out of money, and Starship was developed by flying prototypes until they broke. What changed this year SpaceX going public, and with $SPCX sliding below its IPO price in July when Flight 13 slipped, the short interest climbed significantly, as Teslarati reported at the time. A Starship potentially lost today with revenue generating next-gen Starlink satellites aboard would have landed directly on shareholders.

That pressure showed up after orbit. SpaceX cut a flight planned to last nearly 10 hours to about three, moving splashdown from west of Chile to the North Pacific near Hawaii. SpaceX gave no reason, though Musk said this month the company was being extremely cautious about debris risk. The single Raptor for deorbit worked, and Ship 41 completed its flip and landing burn before breaking apart in the water, an outcome SpaceX expected. Musk has structured SpaceX’s governance to shield long term bets from market pressure.

The payload is the bigger business story. Musk posted that all 26 Starlink V3 satellites deployed and are “operating nominally.” Each V3 is rated for about 1 Tbps of downlink and 160 Gbps of uplink, so this single launch adds roughly 26 Tbps, about 10 times what a Falcon 9 load of V2 Mini satellites adds. The V3 is too large for Falcon 9, making Starship the only vehicle that can build out the planned 100,000 satellite constellation, at up to 60 per flight once it reaches routine service. Unlike the 20 V3 units on Flight 13, which reentered on a suborbital path, these will raise their orbits and could begin serving customers within weeks and bring in hundreds of millions of additional dollars in projected Starlink revenue.

SpaceX has already begun winding down Falcon 9 Starlink launches from Florida in favor of Starship. Reported targets put Flight 15 as early as October 19, leaving about three weeks to diagnose Monday’s engine shutdown before the next orbital attempt.

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Tesla Cybercab fleet doubles to well over 100 units

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(Credit: Teslarati)

Tesla quietly doubled the size of its Cybercab fleet within the Robotaxi program in Austin, Texas, over the weekend to well over 100 units.

The move not only establishes more of the steering-wheel-less and pedal-less vehicles within the ride-sharing fleet Tesla has been operating for a year, but it also solidifies a more robust Robotaxi fleet as a whole.

Riders started receiving notifications from the Robotaxi app that stated: “Cybercab fleet has doubled: more rides available.”

Tesla first launched rides in the Cybercab in early September, although the Robotaxi fleet has been active for over a year, as rides began last Summer. Cybercab is truly Tesla’s most crucial vehicle release yet, as it is the first car any company has built that is geared toward full-fledged and end-to-end autonomy, never needing human intervention for anything.

Only available in Austin at the current time, Cybercab has two seats and has been spotted testing around various U.S. states and regions; Tesla plans to deploy the Cybercab in various U.S. cities in the coming months as a best-case scenario.

Tesla Cybercab gets initial tie-in to localized, in-house cathode plant

The availability of the Cybercab has doubled from just 58 units last Monday to 125 the following Friday. Marking a substantial increase in Cybercab availability, the additional ride-sharing units are more than welcome, as wait times for Cybercabs, especially, were quite high.

The dramatic increase is a sign that demand for Robotaxi is growing and Tesla is feeling more confident that its driverless ride-hailing suite, especially its Full Self-Driving software, is able to handle any traffic situation without explicit direction or supervision from a human being.

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