Tesla appears to have started slowly rolling out v11 of the Full Self-Driving Beta program this morning, just a few days after CEO Elon Musk stated the company would begin releasing it to more vehicles.
Tesla’s FSD Beta v11.3.1 started to roll out to employees late last year and a select few of the automaker’s long-standing testers a few weeks ago.
The controlled rollout allows Tesla to monitor its behaviors and tendencies in a highly safe way, as it can determine issues or bugs in a small sample size and fix them before a wider release begins.
On March 14, Musk stated that “ V11 starts going wide this weekend,” and we’ve heard it before. However, it appears the automaker is happy with the early reviews and is starting to release it to more vehicles.
V11 starts going wide this weekend
— Elon Musk (@elonmusk) March 15, 2023
v11.3.2 is the newest version of the Beta and is being rolled out with Tesla Software Update 2022.45.11. According to statistics from TeslaScope, more vehicles are being updated with the new FSD Beta v11, and more drivers on the r/TeslaMotors subreddit are beginning to report that they have received the update.
Drivers who have experienced the early editions of this rollout have reported that there have been several improvements to highway driving, and inner-city street navigation has also been refined and feels more accurate than ever before, which is undoubtedly a step in the right direction.
The full release notes for the FSD Beta are available below via TeslaScope:
- 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.
- Improved recall for close-by cut-in cases by 15%, particularly for large trucks and high-yaw rate scenarios, through an additional 30k auto-labeled clips mined from the fleet. Additionally, expanded and tuned dedicated speed control for cut-in objects.
- Improved the position of ego in wide lanes, by biasing in the direction of the upcoming turn to allow other cars to maneuver around ego.
- Improved handling during scenarios with high curvature or large trucks by offsetting in lane to maintain safe distances to other vehicles on the road and increase comfort.
- Improved behavior for path blockage lane changes in dense traffic. Ego will now maintain more headway in blocked lanes to hedge for possible gaps in dense traffic.
- Improved lane changes in dense traffic scenarios by allowing higher acceleration during the alignment phase. This results in more natural gap selection to overtake adjacent lane vehicles very close to ego.
- Made turns smoother by improving the detection consistency between lanes, lines and road edge predictions. This was accomplished by integrating the latest version of the lane-guidance module into the road edge and lines network.
- Improved accuracy for detecting other vehicles’ moving semantics. Improved precision by 23% for cases where other vehicles transition to driving and reduced error by 12% for cases where Autopilot incorrectly detects its lead vehicle as parked. These were achieved by increasing video context in the network, adding more data of these scenarios, and increasing the loss penalty for control- relevant vehicles.
- Extended maximum trajectory optimization horizon, resulting in smoother control for high curvature roads and far away vehicles when driving at highway speeds.
- Improved driving behavior next to row of parked cars in narrow lanes, preferring to offset and staying within lane instead of unnecessarily lane changing away or slowing down.
- Improved back-to-back lane change maneuvers through better fusion between vision-based localization and coarse map lane counts.
- Added text blurbs in the user interface to communicate upcoming maneuvers that FSD Beta plans to make. Also improved the visualization of upcoming slowdowns along the vehicle’s path. Chevrons render at varying opacity and speed to indicate the slowdown intensity, and a solid line appears at locations where the car will come to a stop.
- Improved the recall and precision of object detection, notably reducing the position error of semi-trucks by 10%, increasing the recall and precision of crossing vehicles over 100m away by 3% and 7%, respectively, and increasing the recall of motorbikes by 5%. This was accomplished by implementing additional quality checks in our two million video clip autolabeled dataset.
- Reduced false offsetting around objects in wide lanes and near intersections by improving object kinematics modeling in low speed scenarios.
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Tesla has confirmed a crucial detail of its Miami Robotaxi launch, stating that the fleet is operating on an Unsupervised basis, joining a few other cities where company employees do not watch over the vehicles from inside.
Tesla’s Head of AI, Ashok Elluswamy, confirmed the detail on X, answering a highly speculated question about the Robotaxi Service in Miami, which was launched on June 3:
Unsupervised
— Ashok Elluswamy (@aelluswamy) July 3, 2026
The first launch of Robotaxi in Florida, Miami presents a unique opportunity for Tesla as it is operating the Unsupervised Robotaxi ride-hailing service in a major tourist hotspot in the Sunshine State. It also signals the suite will expand to other cities soon; many have requested Orlando, a heavy tourist spot with Disney and other resorts nearby, get access to the program soon as well.
Miami is getting a conservative rollout as well, just as Tesla has done with other cities. The initial geofence covers a compact 10–14 square mile zone in western Miami-Dade County, primarily West Miami extending toward Doral and Sweetwater. It is bounded roughly by SR-826 (Palmetto Expressway) to the north and US-41 (Tamiami Trail) to the south, excluding downtown Miami, Miami Beach, the airport, and most of Coral Gables.
Tesla has also been pretty slim on other details. For example, Tesla has not disclosed the exact fleet size, but field reports and license plate tracking indicate just two unsupervised Model Y vehicles were active on launch day, increasing to three within 48 hours.
According to The Road to Autonomy, a nearby staging lot near Miami International Airport holds dozens of Cybercabs alongside additional Model Y units, suggesting capacity for rapid scaling as demand and data collection grow.
The confirmation of Robotaxi being Unsupervised carries immense weight. It establishes that Tesla’s Miami Robotaxi operations run without human safety drivers or remote supervision, relying entirely on the company’s Full Self-Driving technology. Miami becomes the second major U.S. city after Austin to offer unsupervised Robotaxi rides from day one.
The move reflects rapid progress in Tesla’s AI efforts. Neural networks trained on vast real-world data now handle complex urban environments, including South Florida’s heavy traffic, pedestrians, and rainy conditions. Industry observers see it as validation of Tesla’s vision-centric, data-driven approach versus traditional rule-based systems; a truly unorthodox approach in this day and age.
Challenges remain, including regulatory oversight, public trust, and scaling the fleet to match geofence ambitions. Miami’s small initial footprint and limited vehicles highlight a deliberate, measured expansion strategy focused on safety and data gathering.
Nevertheless, the unsupervised confirmation marks a pivotal milestone. It showcases technical readiness and advances Tesla’s vision of transforming vehicles into autonomous revenue generators while reshaping urban mobility. For Miami users, driverless transportation has moved from concept to reality.
A California radiologist who drove his Tesla Model Y off a 250-foot cliff in an attempt to kill his family has had his charges dismissed after doctors say he is “doing well” in a mental health program.
Dharmesh Patel was charged with three counts of attempted murder in connection with a January 2023 crash where he drove his Tesla off a cliff, injuring his wife and two children, aged 7 and 4 at the time.
Patel drove the Tesla off Devil’s Slide in California, an area that is extremely rough to the point that investigators and rescuers expected the worst when arriving at the scene for the first time. Patel supposedly had schizoaffective disorder, according to Deputy District Attorney Dominique Davis.
Shockingly, Patel’s wife, who was in the vehicle, testified that she did not want her husband to be prosecuted, noting that their children missed their father and they wanted him to come back home. Patel’s attorney argued, “not everyone who commits a crime is a criminal.”
Doctor who took Tesla off cliff gets support from unlikely person
A three-day trial in Mental Health Diversion Court ruled in Patel’s favor, which kept him out of jail and instead on house arrest. He was admitted to a Mental Health Diversion Program, which he successfully completed, the Associated Press reported. San Mateo County District Attorney Steve Wagstaffe said the judge was “required by law” to dismiss the charges:
“If the person who’s given mental health diversion follows the treatment plan, there’s nothing that can be done, and at the end of the two years he gets it wiped out of his record.”
Wagstaffe said he has argued, along with other DAs in California, to have attempted murder removed from the list of charges eligible to be dismissed due to mental health diversion programs.
Patel had the charges officially dismissed on Monday; his wife waited for him as he left court and they departed the building together, according to Mercury News. Patel surrendered his California medical license in December.
The crash has been one of the best examples of Tesla’s incredible engineering, which has saved four lives in this particular instance. The car was totalled but kept the four human beings alive and safe, which is something that many referred to as “an absolute miracle.”
A common misconception of anti-EV proponents is that the batteries used in the vehicles are detrimental to the environment and that they cause more waste than they are worth. But a look at Tesla’s battery recycling efforts last year shows the company is doing more than ever to recover materials and give portions of the cells a second life.
Tesla reported a significant milestone in its sustainability efforts last year, with battery recycling volumes rising 20% compared to 2024. According to the company’s 2025 Impact Report, Tesla recycled over 14,000 metric tons of battery material through a combination of in-house processing at its Gigafactories and collaborations with third-party recycling partners.
Tesla: “In 2025, we recycled over 14,000 metric tons of battery material through a combination of in-house processing and through our network of recycling partners.”
That’s equivalent to 46,000 long-range battery packs, a +20% increase from 2024. pic.twitter.com/TC3Nz7Kaqf
— Sawyer Merritt (@SawyerMerritt) July 7, 2026
This amount of recovered material is equivalent to the resources needed to produce approximately 46,000 long-range battery packs. The increase reflects growing operational scale as Tesla’s global vehicle fleet expands and more batteries reach end-of-life or manufacturing scrap becomes available for processing.
Tesla and Battery Recycling
Battery recycling forms a core part of Tesla’s circular economy strategy. The company designs its batteries for longevity, often exceeding 200,000 miles of driving, and prioritizes repairs, remanufacturing, and second-life applications before full recycling.
Once packs are decommissioned, Tesla ensures 100% are recycled with no materials sent to landfills. This approach recovers critical metals including lithium, nickel, cobalt, and copper, which can be refined and reused in new battery production.
Tesla has advanced hydrometallurgical recycling processes capable of achieving recovery rates up to 98% for key battery metals. These methods are more efficient and environmentally friendly than traditional pyrometallurgical techniques, reducing energy use and enabling higher-purity materials suitable for direct reintegration into battery manufacturing.
Tesla co-founder JB Straubel confirms Redwood’s battery recycling operations are already profitable
In-house capabilities are supplemented by a network of specialized partners, creating a robust system that handles both production scrap and end-of-life packs.
The environmental and economic benefits are substantial. Recycling reduces reliance on virgin mining, lowers the carbon footprint associated with raw material extraction and processing, and helps stabilize supply chains for critical minerals amid rising global EV demand. As millions of Tesla vehicles age, the volume of recyclable material is expected to grow significantly in the coming years.
This 20% year-over-year growth demonstrates the effectiveness of Tesla’s investments in recycling infrastructure and technology. It positions the company as a leader in addressing one of the automotive industry’s major sustainability challenges. Continued innovation in battery design for easier disassembly and higher recyclability will further enhance these efforts.
Overall, Tesla’s progress in 2025 highlights how scaling recycling operations supports both environmental goals and long-term business resilience in the transition to electric mobility. As the EV market matures, such closed-loop systems will become increasingly vital for sustainable growth.
Tesla confirms crucial detail of Miami Robotaxi launch
Radiologist who drove Tesla off cliff has attempted murder charges dismissed
