FSD Beta 10.11 now going out to public testers

By Nuno Cristovao
New vector lanes
New vector lanes
@MarkHalleyPhd/Twitter

Tesla's latest FSD Beta, v10.11 is now going out to public testers. The beta is version 2022.4.5.15. For FSD Beta testers, it'll be the first update they receive that's based on a 2022 release.

Earlier this month Elon tweeted that the beta may go out as early as this past Tuesday. However, he then followed up that it was instead going to go out this past weekend.

Over the weekend we saw FSD Beta 10.11 go out to several employees, which Tesla uses as a final testing phase before releasing to the public.

Today we're finally seeing several public testers getting this build, but it may be a while before it goes out to everyone. Tesla looks at the release carefully as it's going out and can choose to slow it down, speed it up or stop it completely to fix any issues.

When Elon spoke about the next FSD Beta, he mentioned FSD Beta 10.12. This beta is version 10.11. It's not clear whether there was a misunderstanding or whether Tesla initially planned to increment the version.

However, this is a completely new beta for all public testers and it appears to be packed with improvements.

The most notable improvements appear to be new vector-based lanes and reduced slowdowns. An example of the new vector-based lanes is below. In addition to clearer lane markings, it appears that the whole lane will also be highlighted in blue when the car starts to perform a lane change.

New vector lanes
New vector lanes
@MarkHalleyPhd/Twitter

This beta is expected to hit Canada for the first time according to Elon, but there are no signs yet of it going north of the border.

Tesla will likely monitor it for several days in the US before releasing it to our northern neighbor.

The complete FSD Beta release notes are below:

- Upgraded modeling of lane geometry from dense rasters ("bag of points") to an autoregressive decoder that directly predicts and connects "vector space" lanes point by point using a transformer neural network. This enables us to predict crossing lanes, allows computationally cheaper and less error prone post-processing, and paves the way for predicting many other signals and their relationships jointly and end-to-end.

- Use more accurate predictions of where vehicles are turning or merging to reduce unnecessary slowdowns for vehicles that will not cross our path.

- Improved right-of-way understanding if the map is inaccurate or the car cannot follow the navigation. In particular, modeling intersection extents is now entirely based on network predictions and no longer uses map-based heuristics.

- Improved the precision of VRU detections by 44.9%, dramatically reducing spurious false positive pedestrians and bicycles (especially around tar seams, skid marks, and rain drops). This was accomplished by increasing the data size of the next-gen autolabeler, training network parameters that were previously frozen, and modifying the network loss functions. We find that this decreases the incidence of VRU-related false slowdowns.

- Reduced the predicted velocity error of very close-by motorcycles, scooters, wheelchairs, and pedestrians by 63.6%. To do this, we introduced a new dataset of simulated adversarial high speed VRU interactions. This update improves autopilot control around fast-moving and cutting-in VRUs.

- Improved creeping profile with higher jerk when creeping starts and ends.

- Improved control for nearby obstacles by predicting continuous distance to static geometry with the general static obstacle network.

- Reduced vehicle "parked" attribute error rate by 17%, achieved by increasing the dataset size by 14%. Also improved brake light accuracy.

- Improved clear-to-go scenario velocity error by 5% and highway scenario velocity error by 10%, achieved by tuning loss function targeted at improving performance in difficult scenarios.

- Improved detection and control for open car doors.

- Improved smoothness through turns by using an optimization-based approach to decide which road lines are irrelevant for control given lateral and longitudinal acceleration and jerk limits as well as vehicle kinematics.

- Improved stability of the FSD Ul visualizations by optimizing ethernet data transfer pipeline by 15%.

- Improved recall for vehicles directly behind ego, and improved precision for vehicle detection network.

Release Notes Explained

Here is a great video that explains Tesla's technical release notes and what improvements you can find in this release.

In addition to the improvements in this FSD Beta, testers can also expect to find these other features that were added in the 2022.4 update.

Range Display Calibration for LFP batteries

If you have a SR+ with an LFP battery, then you'll also receive this feature that charges your car to 100% to help improve battery calibration. LFP batteries have very similar voltages from a low state of charge to a high state of charge. If the battery isn't regularly charged to 100%, it can be difficult for the vehicle to know its state of charge, which could cause some issues.

Cabin Camera

Tesla is collecting additional analytics from the cabin camera to help develop additional features. Tesla is asking you to opt-in to cabin camera analytics if you'd like to help develop new features.

There's no word on what these new features may be, but it could be just about anything, such as the ability to send you a notification if it detects an animal in your car and you forgot to turn on Dog Mode.

Car Colorizer

We're probably all familiar with this feature by now that allows you to alter the exterior color of your vehicle. The color you pick is used in the car's visualizations, car menus and in the Tesla app. You can also view a video of Tesla's Car Colorizer feature.

Audio Sources

The ability to disable certain audio sources comes back in 2022.4. If there are audio sources that you don't use, such as TIDAL, Spotify, or TuneIn, you can now disable them.

When an audio source is disabled, it won't appear in the More Apps menu or in the Sources dropdown.

Icons in the Status Bar

2022.4 was released quite a while ago, so it's easy for FSD Beta testers to forget everything that is in this release and why they should be excited.

Some icons are now returning to the car's top status bar, such as Driver Profiles (while in park) and the Sentry Mode icon.

Save Dashcam Clips

You can now more easily save dashcam clips if you have the Dashcam viewer in your launcher. Since the dashcam viewer can't be used while driving, the icon now has a dual purpose. If you tap it while in Drive, your car will save the last ten minutes of footage.

Regenerative Braking in Autopilot

Additional regenerative braking is now used in Autopilot, which will be especially useful in FSD. The vehicle previously used regenerative braking while on AP, but it will now apply it at lower speeds that better match how a driver would use regenerative braking.

Windshield Wiper Defrost

If you have a new Tesla that was built in the past few months, then it may have windshield wiper heaters. If it does, then this is the software update that enables it.

Nearby Superchargers

You can once again view nearby Superchargers in the same way you could in Tesla's v10 software. The Superchargers icon now appears on the far side just like it used to.

This FSD Beta release is an exciting one that includes many new features with the updated FSD Beta build and in the public 2022.4 release. You can also view the full 2022.4 release notes.

Tesla Updates Robotaxi App: Adds Adjustable Pick Up Locations, Shows Wait Time and More [VIDEO]

By Karan Singh
Nic Cruz Patane

Tesla is rolling out a fairly big update for its iOS and early-access-only Robotaxi app, delivering a suite of improvements that address user feedback from the initial launch last month. The update improves the user experience with increased flexibility, more information, and overall design polish.

The most prominent feature in this update is that Tesla now allows you to adjust your pickup location. Once a Robotaxi arrives at your pickup location, you have 15 minutes to start the ride. The app will now display the remaining time your Robotaxi will wait for you, counting down from 15:00. The wait time is also shown in the iOS Live Activity if your phone is on the lock screen.

How Adjustable Pickups Work

We previously speculated that Tesla had predetermined pickup locations, as the pickup location wasn’t always where the user was. Now, with the ability to adjust the pickup location, we can clearly see that Tesla has specific locations where users can be picked up.

Rather than allowing users to drop a pin anywhere on the map, the new feature works by having the user drag the map to their desired area. The app then presents a list of nearby, predetermined locations to choose from. Once a user selects a spot from this curated list, they hit “Confirm.” The pickup site can also be changed while the vehicle is en route.

This specific implementation raises an interesting question: Why limit users to predetermined spots? The answer likely lies in how Tesla utilizes fleet data to improve its service.

Release Notes

While the app is still only available on iOS through Apple’s TestFlight program, invited users can download and update the app.

Tesla included these release notes in update 25.7.0 of the Robotaxi app:

  • You can now adjust pickup location

  • Display the remaining wait time at pickup in the app and Live Activity

  • Design improvements

  • Bug fixes and stability improvements

Nic Cruz Patane

Why Predetermined Pick Up Spots?

The use of predetermined pickup points is less of a limitation and more of a feature. These curated locations are almost certainly spots that Tesla’s fleet data has identified as optimal and safe for an autonomous vehicle to perform a pickup or drop-off.

This suggests that Tesla is methodically “mapping” its service area not just for calibration and validation of FSD builds but also to help perform the first and last 50-foot interactions that are critical to a safe and smooth ride-hailing experience.

An optimal pickup point likely has several key characteristics identified by the fleet, including:

  • A safe and clear pull-away area away from traffic

  • Good visibility for cameras, free of obstructions

  • Easy entry and exit paths for an autonomous vehicle

This change to pick-up locations reveals how Tesla’s Robotaxi Network is more than just Unsupervised FSD. There are a lot of moving parts, many of which Tesla recently implemented, and others that likely still need to be implemented, such as automated charging.

Frequent Updates

This latest update delivers a much-needed feature for adjusting pickup locations, but it also gives us a view into exactly what Tesla is doing with all the data it is collecting with its validation vehicles rolling around Austin, alongside its Robotaxi fleet.

Tesla is quickly iterating on its app and presumably the vehicle’s software to build a reliable and predictable network, using data to perfect every aspect of the experience, from the moment you hail the ride to the moment you step out of the car.

Tesla Will Face $2 Billion in Lost Profit as 'Big Beautiful Bill' Kills EV Credits

By Karan Singh
Not a Tesla App

The massive legislative effort titled the "Big Beautiful Bill" is taking direct aim at what has become one of Tesla’s most critical and profitable revenue streams: the sale of US regulatory credits. The bill could eliminate billions of dollars from Tesla’s bottom line each year and will slow down the transition to electric vehicles in the US.

The financial stakes for Tesla are absolutely immense. In 2024, Tesla generated $2.76 billion from selling these credits. This high-margin revenue was the sole reason Tesla posted a profit in Q1 2025; without the $595 million from regulatory credits, Tesla’s reported $409 million in profit would have been a $189 million loss.

How the ZEV Credit System Works

Zero-Emission Vehicle (ZEV) credits are part of state-level programs, led by California, designed to accelerate the adoption of electric vehicles. Each year, automakers are required to hold a certain number of ZEV credits, with the amount based on their total vehicle sales within that state. Under this system, automakers that fail to sell a certain percentage of zero-emission vehicles must either pay a significant fine or purchase credits from a company that exceeds the mandate.

Automakers who fail to sell enough EVs to meet their quota have a deficit and face two choices: pay a hefty fine to the state government for each missing credit (for example, $5,000 per credit in California) or buy credits from a company with a surplus.

As an all-EV company, Tesla generates a massive surplus of these credits. It can then turn around and sell them to legacy automakers at prices cheaper than the fine, creating a win-win scenario: the legacy automaker avoids a larger penalty, and Tesla gains a lucrative, near-pure-profit revenue stream. 

This new bill will dismantle this by eliminating the financial penalties for non-compliance, which would effectively make Tesla’s credits worthless. While the ZEV program is a state law, the Big Beautiful Bill will fully eliminate the penalties at a federal level.

A Multi-Billion Dollar Impact

The removal of US ZEGV credits would be a severe blow to Tesla’s financials. One JPMorgan analyst estimated that the move could reduce Tesla’s earnings by over 50%, representing a potential annual loss of $2 billion. While Tesla also earns similar credits in Europe and China, analysts suggest that 80-90% of its credit revenue in Q1 2025 came from US programs. 

Why the Program Exists

While the impact on Tesla would be direct and immediate, the credit system has a wider purpose. It creates a strong financial incentive for legacy automakers to develop and accelerate their zero-emission vehicle programs, whether it’s hydrogen, electric, or another alternative.

Eliminating the need for these credits would remove that financial pressure. This could allow traditional automakers to slow their EV transition in the US without the fear of a financial penalty, potentially leading to fewer EV choices for consumers and a slower path to vehicle electrification in the country.

Big, But Not Beautiful

On Sunday Morning TV, Elon Musk was asked his thoughts on the Big Beautiful Bill. They were pretty simple. A bill could be big, or it could be beautiful - I don’t know if it can be both, Musk stated.

The bill poses a threat to Tesla’s bottom line and to the adoption of EVs in the US market, where automakers will no longer have a financial incentive to transition to cleaner vehicles, a market they’ve regularly struggled in when competing against Tesla.

Tesla will have to work carefully in the future to cut expenses to remain profitable after the elimination of these regulatory credits.

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