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Tesla is patenting a clever way to train Autopilot with augmented camera images
Tesla is currently tackling what could only be described as its biggest challenge to date. In his Master Plan, Part Deux, CEO Elon Musk envisioned a fleet of zero-emissions vehicles that are capable of driving on their own. Tesla has made steps towards this goal with improvements and refinements to its Autopilot and Full Self-Driving suites, but a lot of work remains to be done.
As noted by Tesla during its Autonomy Day presentation last year, attaining Full Self-Driving is largely a matter of training the neural networks used by the company. Tesla adopts what could be described as a somewhat organic approach for autonomy, with the company using a system that is centered on cameras and artificial intelligence — the equivalent of a human primarily using the eyes and brain to drive.
Tesla’s camera-centric approach may be quite controversial due to Elon Musk’s strong stance against LiDAR, but it is gaining ground, with other autonomous vehicle companies such as MobilEye developing FSD systems that rely primarily on visual data and a trained neural network. This approach does come with its challenges, as training neural networks requires tons of data. Tesla emphasized this point as much during its Autonomy Day presentation.
With this in mind, it is pertinent for the electric car maker to train its neural networks in a way that is as efficient as possible with zero compromises. To help accomplish this, Tesla seems to be looking into the utilization of augmented data, as described in a recently published patent titled “Systems and Methods for Training Machine Models with Augmented Data.”
Teslas are equipped with a suite of cameras that provide 360-degree visual coverage for the vehicle. In the patent’s description, Tesla noted that images used for neural network training are usually captured by various sensors, which, at times, have different characteristics. An example of this may lie in a Tesla’s three forward-facing cameras, each of which has a different field of view and range as the other two.
Tesla’s recent patent describes a system that allows the company to process these images in an optimized manner. Part of how this is done is through augmentation, which opens the doors to flexible and widespread neural network training, even when it involves vehicles equipped with differently-specced cameras. The electric car maker describes this process as such:
“Augmentation may provide generalization and greater robustness to the model prediction, particularly when images are clouded, occluded, or otherwise do not provide clear views of the detectable objects. These approaches may be particularly useful for object detection and in autonomous vehicles. This approach may also be beneficial for other situations in which the same camera configurations may be deployed to many devices. Since these devices may have a consistent set of sensors in a consistent orientation, the training data may be collected with a given configuration, a model may be trained with augmented data from the collected training data, and the trained model may be deployed to devices having the same configuration.”
Among the most notable aspects of Tesla’s recent patent is the use of “cutouts,” which allow Tesla’s neural networks to be trained using an optimized set of images. This was something that was discussed by former Tesla Autopilot engineer Eshak Mir in a Third Row Podcast interview, where he hinted at a system adopted in the electric car maker’s ongoing Autopilot rewrite that helped lay out “all the camera images” from a vehicle “into one view.” Such a process has the potential to help Tesla with 3D labeling, especially since the images used for neural network training are stitched together. Tesla’s patent seems to reference a system that is very similar to that described by the former Autopilot engineer.
“As a further example, the images may be augmented with a“cutout” function that removes a portion of the original image. The removed portion of the image may then be replaced with other image content, such as a specified color, blur, noise, or from another image. The number, size, region, and replacement content for cutouts may be varied and may be based on the label of the image (e.g., the region of interest in the image, or a bounding box for an object).”
Tesla is aiming to release a feature-complete version of its Full Self-Driving suite as soon as possible. Elon Musk remains optimistic about this, despite the company missing its initial timeline that was set at the end of 2019. That being said, Elon Musk did mention previously that Tesla is working on a foundational rewrite of Autopilot. In a tweet early last month, Musk stated that an essential part of the rewrite involves work on Autopilot’s core foundation code and 3D labeling. Once done, the CEO indicated that additional functionalities could be rolled out quickly. This recent patent, if any, seems to give a glimpse at how these improvements are being done.
Tesla has expanded the footprint of a massive safety feature worldwide with a recent Software Update labeled as 2026.20.6. The expansion of the “Blind Spot Warning While Parked” feature represents the more widespread availability of the feature, which aims to prevent “dooring.”
Dooring is when a driver or passenger opens a car door into the path of an oncoming road user, usually a cyclist or motorcyclist. It is among the most common types of cycling accidents, the League of American Bicyclists says.
For this reason, Tesla created a feature that warns occupants not to open the door because an object is approaching. The feature will sound a chime, and it will also delay the opening of the door to prevent an incident.
The release notes state (via Not a Tesla App):
“If you attempt to open a door while an approaching object is detected in your blind spot (for example, a bicyclist approaching from behind) a chime sounds, and your door will not open upon initial button press. Wait a short time and press the button a second time to override the warning.”
Tesla initially rolled out this feature back in 2024 with the Model 3 “Highland.” However, it remained with the Model 3 exclusively for over a year; that was until Tesla added it to the Cybertruck this past Spring.
Now, it is making its way to the new Model Y, 2021 and newer Model S, and 2021 or newer Model X.
The prevention of dooring incidents could eliminate many injuries to cyclists, especially in an urban setting. Dooring accounts for 10-20 percent of bike-related crashes in major cities, and over 17,000 dooring-related incidents were treated in the U.S. over the course of a decade. These usually involve fractures, contusions, and head trauma.
Tesla confirmed this morning that it has sent the first production units, manufactured with no steering wheel or pedals, to on-road testing in Austin, sharing video of the first rides with no human controls.
The lack of steering wheels and pedals in the Cybercab aligns with Tesla’s self-certification of Robotaxi as Level 4 SAE, a platform it plans to make widespread through internal vehicles and customer-owned cars that will operate and generate revenue for individuals.
The start of these engineering tests is a major signal for Tesla, which plans to bring driverless, wheel-less, and pedal-less Cybercabs to market in the coming months. With production already well underway at Gigafactory Texas, where the Cybercab is built, there is some inclination to believe the first public rides could happen sooner rather than later.
Engineering tests of the first production Cybercab have begun in Austin pic.twitter.com/fk3KQvcE8a
— Tesla (@Tesla) June 30, 2026
Tesla’s engineering tests will put the Cybercab in real-world scenarios, testing not only the hardware, but more importantly, the software that drives the car around Austin with nobody supervising it within the car.
This is perhaps the biggest part of the internal testing process, especially prior to allowing regular, everyday people to hail the Cybercab for an autonomous ride. These early rides serve as a true benchmark for Tesla: How many rides can it achieve safely? How many miles did it travel consecutively without needing an intervention? What scenarios challenge the Full Self-Driving suite the most?
The proper precautions have already been put into place as well, as Tesla released the First Responders Guide to Cybercab over the weekend, ensuring that emergency services have 24/7 access to Robotaxi Assistance, as well as other boundaries, such as Geofencing features that can be used to redirect autonomous vehicle traffic due to accidents, road closures, construction, or maintenance.
Cybercab seems genuinely close to being added to the Robotaxi fleet in Austin, but Tesla has prioritized safety throughout this entire process. Therefore, we think it could be months before it truly starts giving rides to the public. People have been frustrated with this, but Robotaxi in Austin has a tremendous safety record so far, so the slow rollout has kept people safe and accidents to a minimum.
The most important thing is that Tesla continues to show consistent progress in the Cybercab’s ramp-up toward fleet addition. A few weeks back, we saw the EPA reward the Cybercab a Certificate of Conformity, allowing it to enter the stream of commerce. Then, we saw Tesla add decals, signaling that it was likely about to start testing it publicly. That has now happened.
The next big move will be the announcement of the first rides, so this Summer should be filled with anticipation.
For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.
Would you buy a Tesla phone ? pic.twitter.com/aaTwvvIJit
— Tesla Owners Silicon Valley (@teslaownersSV) October 6, 2023
Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.
It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.
Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.
The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.
Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.
The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.
SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.
There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.
The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.
Tesla expands massive safety feature worldwide in latest update
Tesla sends production Cybercab with no steering wheel, pedals to on-road testing
