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.
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 lands approval for Robotaxi operation in third U.S. state
On Tuesday, Tesla officially received regulatory approval from the State of Arizona, making it the third state for the company to receive approval in.
Tesla has officially landed approval to operate its Robotaxi ride-hailing service in its third U.S. state, as it has landed a regulatory green light from the State of Arizona’s Department of Transportation.
Tesla has been working to expand to new U.S. states after launching in Texas and California earlier this year. Recently, it said it was hoping to land in Nevada, Arizona, and Florida, expanding to five new cities in those three states.
On Tuesday, Tesla officially received regulatory approval from the State of Arizona, making it the third state for the company to receive approval in:
BREAKING: Tesla has officially received approval from the Arizona Department of Transportation to launch its Robotaxi service on public roads in the state!
I just confirmed directly with the Arizona DOT that @Tesla applied for a Transportation Network Company permit on Nov 13th.… pic.twitter.com/iKbwfGfiju
— Sawyer Merritt (@SawyerMerritt) November 18, 2025
Tesla has also been working on approvals in Nevada and Florida, and it has also had Robotaxi test mules spotted in Pennsylvania.
The interesting thing about the Arizona approval is the fact that Tesla has not received an approval for any specific city; it appears that it can operate statewide. However, early on, Tesla will likely confine its operation to just one or two cities to keep things safe and controlled.
Over the past few months, Robotaxi mules have been spotted in portions of Phoenix and surrounding cities, such as Scottsdale, as the company has been attempting to cross off all the regulatory Ts that it is confronted with as it attempts to expand the ride-hailing service.
It appears the company will be operating it similarly to how it does in Texas, which differs from its California program. In Austin, there is no Safety Monitor in the driver’s seat, unless the route requires freeway travel. In California, there is always a Safety Monitor in the driver’s seat. However, this is unconfirmed.
Earlier today, Tesla enabled its Robotaxi app to be utilized for ride-hailing for anyone using the iOS platform.
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Tesla ride-hailing Safety Monitor dozes off during Bay Area ride
We won’t try to blame the camera person for the incident, because it clearly is not their fault. But it seems somewhat interesting that they did not try to wake the driver up and potentially contact Tesla immediately to alert them of the situation.
A Tesla Robotaxi Safety Monitor appeared to doze off during a ride in the California Bay Area, almost ironically proving the need for autonomous vehicles.
The instance was captured on camera and posted to Reddit in the r/sanfrancisco subreddit by u/ohmichael. They wrote that they have used Tesla’s ride-hailing service in the Bay Area in the past and had pleasant experiences.
However, this one was slightly different. They wrote:
“I took a Tesla Robotaxi in SF just over a week ago. I have used the service a few times before and it has always been great. I actually felt safer than in a regular rideshare.
This time was different. The safety driver literally fell asleep at least three times during the ride. Each time the car’s pay attention safety alert went off and the beeping is what woke him back up.
I reported it through the app to the Robotaxi support team and told them I had videos, but I never got a response.
I held off on posting anything because I wanted to give Tesla a chance to respond privately. It has been more than a week now and this feels like a serious issue for other riders too.
Has anyone else seen this happen?”
My Tesla Robotaxi “safety” driver fell asleep
byu/ohmichael insanfrancisco
The driver eventually woke up after prompts from the vehicle, but it is pretty alarming to see someone like this while they’re ultimately responsible for what happens with the ride.
We won’t try to blame the camera person for the incident, because it clearly is not their fault. But it seems somewhat interesting that they did not try to wake the driver up and potentially contact Tesla immediately to alert them of the situation.
They should have probably left the vehicle immediately.
Tesla’s ride-hailing service in the Bay Area differs from the one that is currently active in Austin, Texas, due to local regulations. In Austin, there is no Safety Monitor in the driver’s seat unless the route requires the highway.
Tesla plans to remove the Safety Monitors in Austin by the end of the year.
Tesla has officially opened Robotaxi access to everyone and everyone, but there is one catch: you have to have an iPhone.
Tesla’s Robotaxi service in Austin and its ride-hailing service in the Bay Area were both officially launched to the public today, giving anyone using the iOS platform the ability to simply download the app and utilize it for a ride in either of those locations.
It has been in operation for several months: it launched in Austin in late June and in the Bay Area about a month later. In Austin, there is nobody in the driver’s seat unless the route takes you on the freeway.
In the Bay Area, there is someone in the driver’s seat at all times.
The platform was initially launched to those who were specifically invited to Austin to try it out.
Tesla confirms Robotaxi is heading to five new cities in the U.S.
Slowly, Tesla launched the platform to more people, hoping to expand the number of rides and get more valuable data on its performance in both regions to help local regulatory agencies relax some of the constraints that were placed on it.
Additionally, Tesla had its own in-house restrictions, like the presence of Safety Monitors in the vehicles. However, CEO Elon Musk has maintained that these monitors were present for safety reasons specifically, but revealed the plan was to remove them by the end of the year.
Now, Tesla is opening up Robotaxi to anyone who wants to try it, as many people reported today that they were able to access the app and immediately fetch a ride if they were in the area.
We also confirmed it ourselves, as it was shown that we could grab a ride in the Bay Area if we wanted to:
🚨 Tesla Robotaxi ride-hailing Service in Austin and the Bay Area has opened up for anyone on iOS
Go download the app and, if you’re in the area, hail a ride from Robotaxi pic.twitter.com/1CgzG0xk1J
— TESLARATI (@Teslarati) November 18, 2025
The launch of a more public Robotaxi network that allows anyone to access it seems to be a serious move of confidence by Tesla, as it is no longer confining the service to influencers who are handpicked by the company.
In the coming weeks, we expect Tesla to then rid these vehicles of the Safety Monitors as Musk predicted. If it can come through on that by the end of the year, the six-month period where Tesla went from launching Robotaxi to enabling driverless rides is incredibly impressive.
Tesla lands approval for Robotaxi operation in third U.S. state
Tesla ride-hailing Safety Monitor dozes off during Bay Area ride
