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.
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Lifestyle
NTSB findings on fatal Tesla crash tell a very different story
The NTSB confirmed the driver, not Tesla’s FSD, caused the fatal Texas house crash.
The National Transportation Safety Board released preliminary findings Wednesday confirming that a Tesla driver, not the vehicle’s software, caused a fatal crash in Katy, Texas in June. The driver, 44-year-old Michael Butler, had engaged Full Self-Driving Supervised mode on Rose Hollow Lane, a residential street with a 30 mph speed limit, before manually overriding the system by pressing the accelerator pedal all the way to 100%. Data recovered from the 2025 Tesla Model 3 showed the vehicle was traveling over 70 miles per hour when it struck a home and killed 76-year-old Martha Avila, who was inside. Weather was clear, the road was dry, and it was daylight.
Texas man charged in fatal Tesla crash where he blamed Autopilot
Butler told authorities he had passed out at the wheel. But security camera footage obtained by the NTSB told a different story, and showed the car accelerating through an intersection before leaving the road entirely. Police also found that Butler’s phone had Google searches including the terms “Tesla FSD not aggressive enough 2026” and “Tesla FSD too timid,” raising serious questions about how he was using the system before the crash. Butler has since been charged with manslaughter. The victim’s family has filed a lawsuit against both Butler and Tesla, alleging negligence.
The NTSB findings aligned directly with what Tesla VP of AI Software Ashok Elluswamy had already stated publicly on X in the weeks after the crash, writing that “the driver manually overrode self-driving by pressing the accelerator all the way to 100%.” The data confirmed his account.
Yup. In this case, the driver manually overrode self-driving by pressing the accelerator all the way to 100% of the accel pedal in this residential area. They reached a speed of 73 mph during the crash, and had the accelerator pressed even after the crash.
— Ashok Elluswamy (@aelluswamy) June 22, 2026
Lucid CEO Silvio Napoli responded to rumors of an imminent bankruptcy that was reportedly being mulled after a report stated the automaker was working with the firm AlixPartners to iron out its next steps.
The company felt a massive loss on Wall Street yesterday, as the report essentially pushed the stock down as much as 55 percent on Tuesday.
The report, published initially by Eletric-Vehicles.com, claimed Lucid was essentially in dire straits and was told by AlixPartners, a commonly used restructuring advisor, to either take shares private or file for Chapter 11 bankruptcy protection.
Lucid’s head of Communications, Nick Twork, immediately challenged the report and stated the company “has sufficient liquidity to carry its operations well into next year.”
Now, the company’s CEO is chiming in as well, stating that the report is “so far from the facts that they require a direct response.”
Napoli said:
“Lucid is not considering bankruptcy or a transaction to take the company private. Those reports are false. The Board did not explore either scenario. Period.
As disclosed in our most recent quarterly filing, Lucid has sufficient liquidity to fund its operations well into next year.
We work with outside advisors to improve operational performance and execution. They are not advising Lucid on a take-private transaction or bankruptcy, and any suggestion that they have recommended either course of action to management or the Board is false.
My priority is clear: turn this company around. That is where the leadership team and I are focused.
I look forward to providing a full update during our quarterly earnings call on August 4th.”
🚨 Lucid CEO Silvio Napoli calls rumors of financial issues “so far from the facts that they require a direct response.”
Read his full remarks here: https://t.co/t3Pg1NHvzy pic.twitter.com/LvHUPhO4Qf
— TESLARATI (@Teslarati) July 15, 2026
It seems pretty clear that Lucid is confident things will be okay, and, to be honest, they should not have much to worry about, especially considering the company has been backed by the Saudi Public Investment Fund (PIF) for years. It has solid financial backing, and its sales, while weak, are pretty much right on par with a company of this age.
Lucid also sent a Cease & Desist letter to the publication for their report.
Lucid shares have rebounded nicely and are up nearly 21 percent at the time of publication. As soon as the company dispelled the rumors of bankruptcy yesterday, the stock began to climb back toward more reasonable levels.
Tesla has once again demonstrated strong customer focus by swiftly addressing and fully refunding a bizarre Supercharger pricing glitch that affected drivers in Atlantic Canada.
The issue surfaced earlier this month when the Tesla app began displaying dramatically inflated per-minute charging rates at stations in Prince Edward Island and parts of New Brunswick.
One widely shared screenshot from a Charlottetown, PEI Supercharger showed rates reaching ridiculous levels: $6.00 per minute for the 180-250 kW tier, along with $3.57/min for 100-180 kW and $2.29/min for 60-100 kW.
Correct pricing will be going live at midnight tonight. All fees since July 2nd 2026 will be waived.
— Tesla Charging (@TeslaCharging) July 13, 2026
These figures were several times higher than normal Supercharger pricing in the region.
To put the error in perspective, charging at the highest incorrect rate would have been shockingly expensive.
At 250 kW, a common charging speed at Superchargers, a vehicle pulls roughly 4.17 kWh per minute. Under the glitch, a driver spending just 10 minutes at peak power would face a $60 bill. A typical 20- to 30-minute session to add meaningful range could have cost $120 to $180 or more, before any congestion fees.
Tesla gets another layer of gamification with Free Supercharging on the line
By comparison, standard Canadian Supercharger rates usually fall between $0.25 and $0.60 per kWh, making a similar session cost roughly $15–$40. The erroneous per-minute structure, combined with the inflated numbers, turned what should be a convenient stop into a potential financial shock.
The glitch appears to have started sometime around early July, and quickly drew attention on social media as owners questioned whether Tesla had implemented steep hidden increases. Some drivers even reported seeing $0 charges in their history, indicating broader billing confusion.
Tesla’s official Charging account on X stated that correct pricing would roll out at midnight on July 13, so the fix is already in effect. More importantly, the company announced it would waive all fees for every Supercharger session since July 2. This blanket waiver covers the entire affected period without requiring users to file individual claims, with automated refunds expected soon. The decision affects stations in PEI and nearby areas in New Brunswick and Nova Scotia.
It’s a classy move, and rather than issuing partial credits or forcing owners to submit support tickets, Tesla simply absorbed the cost of the system error and made drivers whole. In an industry where hidden fees and bill disputes are common, Tesla’s proactive, no-questions-asked approach reinforces owner trust and highlights the company’s commitment to service excellence.
The incident, while disruptive for a short time, ultimately showcases Tesla’s ability to own mistakes and prioritize customer satisfaction. Atlantic Canada Tesla owners can now charge with confidence again, knowing the company has their back when technology glitches occur.
In an era of complex EV billing, such transparency and generosity are refreshing and set a positive example for the industry.
NTSB findings on fatal Tesla crash tell a very different story
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