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Tesla patents virtualization and machine learning software to improve FSD

Credit: Drive in EV/Twitter

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Tesla has applied for a set of patents that are set to significantly improve virtualization, recognition, and Full Self Driving overall.

Tesla has worked tirelessly to improve full self-driving technology in the first two months of the year. Most recently, Tesla pushed its most significant improvement to employees, v11.3. Still, with new patented technology, the software is set to continue to improve dramatically this year. The two patents, focusing on virtualization and machine learning, appeared in the U.S. Patent Office database late last week.

The first patent, “Vision-Based Machine Learning Model for Autonomous Driving with Adjustable Virtual Camera,” is likely simply a reworking of a previous system but changed to fit Tesla’s new visual-only autonomous driving system. The second patent, “Vision-Based Machine Learning Model for Aggregation of Static Objects and Systems for Autonomous Driving,” focuses more on improving the virtualization seen on screen while in the vehicle.

The first patent’s abstract describes a system that looks similar to the one already available in Tesla vehicles but has been adapted to remove non-visual sensors. However, it does include an added “adjustable virtual camera,” potentially indicating that Tesla is working to give drivers more control of looking out of their car with the camera system or improved virtualization interaction.

“Systems and methods for a vision-based machine learning model for autonomous driving with adjustable virtual camera. An example method includes obtaining images from a multitude of image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a first portion of a machine learning model. The features are projected into a vector space associated with a virtual camera at a particular height. The projected features are aggregated with other projected features associated with prior images.”

The second, significantly more extensive patent is described in its abstract, focusing on the “aggregation of static objects” by the vehicle:

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“Systems and methods for a vision-based machine learning model for aggregation of static objects and systems for autonomous driving. An example method includes obtaining images from image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a machine learning model. The features are projected into a vector space associated with a birds-eye view based on the machine learning model.”

If anything, the new patents from Tesla show just how dedicated it is to its visual-only system. Nowhere in either of the patents does the automaker address other sensor inputs, which seems to line up with recent discoveries showing upcoming vehicles without ultrasonic sensors.

Further, with Tesla’s increasing focus on making vehicles more AI capable, implementing improved machine learning also matches its design goals.

It remains unclear whether these improvements have been implemented in upcoming software versions or have already been placed in cars via recent software updates. Still, they nonetheless indicate that the company is making continuous progress in its pursuit.

As more and more automakers enter the autonomous driving competition, Tesla’s lead becomes ever more apparent. And while many have mocked the company for its dedication to AI over just vehicles, that investment is proving to be a fantastic one. Hopefully, it will result in an increasingly better Tesla driving experience in the coming years.

What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!

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Will is an auto enthusiast, a gear head, and an EV enthusiast above all. From racing, to industry data, to the most advanced EV tech on earth, he now covers it at Teslarati.

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Tesla Robotaxi will be a 24/7 service: here’s when

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Credit: @AdanGuajardo/X

Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.

The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.

That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.

Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.

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Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.

By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.

Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.

Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.

If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.

That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.

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Tesla Full Self-Driving will now overtake manual driving to avoid disaster

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Credit: Tesla

Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.

Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.

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The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.

The intervention is meant as a last-resort safety net, not a replacement for attentive driving.

Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.

After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.

The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.

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Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.

The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.

If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.

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Tesla Cybercab launch catches NHTSA’s attention who wants to know more

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(Credit: Teslarati)

Tesla launched the all-electric, steering wheel-less, and pedal-less Cybercab last night at a quiet and small event in downtown Austin, Texas.

The launch, which marked the beginning of unsupervised ride-hailing for Tesla’s Robotaxi platform with Cybercab, has already caught the attention of the National Highway Traffic Safety Administration (NHTSA) who has more questions.

NHTSA opened an Audit Query (AQ) into the Cybercab’s Federal Motor Vehicle Safety Standards (FMVSS) certification that Tesla gave the vehicle. Manufacturers self-certify vehicles much of the time to avoid excessive regulatory delays.

Tesla Cybercab interior, note the lack of steering wheel and pedals. (Credit: @niccruzpatane/X< /a>)

However, the agency needs more information; it said in a summary:

“On September 3, 2026, Tesla began commercial deployment with a small number of its Cybercab vehicles in Austin, Texas. Tesla notified the Agency that it certified those Cybercab vehicles as compliant with all applicable Federal Motor Vehicle Safety Standards (FMVSS). Tesla also notified the Agency that it plans to gradually expand commercial deployment of the Cybercab to include additional vehicles and locations.”

It also went on to state that the Cybercab lacks traditional automotive controls, which is a groundbreaking move. The process is entirely new to the NHTSA, which gives the agency some leverage to put Tesla’s launch under a microscope:

“The vehicles lack permanently attached, conventional manual controls, such as a brake pedal, gas pedal, steering wheel, and mirrors. NHTSA is opening this AQ to examine the process and technical data on which Tesla relied when certifying the Cybercab and related issues. Among other things, NHTSA will consider the extent to which Tesla’s certification depended on determinations that certain FMVSS are inapplicable to the Cybercab.”

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Tesla has added 45 Cybercab units to its fleet of Robotaxi-enabled cars in Austin, according to public documents the company submitted to the State of Texas over the past week. Enabling this level of self-driving is something Tesla has worked toward for many years, and now that it is finally here, it seems more than reasonable that regulatory agencies will have some questions.

Many outlets might try to frame this as a negative, but it is truly an agency looking to gain more information about groundbreaking tech that Tesla has been developing for years.

In an effort to keep riders, pedestrians, and property safe, any and all data accumulated from these first days, weeks, and months of rides will likely be shared with the NHTSA to enable broader rollout strategies across the United States and more in the future.

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