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Tesla Smart Summon patent highlights progress in 3D labeling for full self-driving features
A recently published Tesla patent application details the machine learning methods behind Smart Summon, specifically highlighting the progress being made with 3D labeling in training data.
The application, titled “Autonomous and User Controlled Vehicle Summon to a Target,” utilizes machine learning methods explicitly detailed in two other recent Tesla patent publications in its functionality. This series of three inventions altogether describes an automated way of generating training data which is then used by a machine learning model to accomplish an expansive list of self-driving capabilities in Summon.
“Traditionally, much of the effort to curate a training data set is done manually by reviewing potential training data and properly labeling the features associated with the data,” Tesla’s first application in the series states. “The effort required to create a training set with accurate labels can be significant and is often tedious… Therefore, there exists a need to improve the process for generating training data with accurate labeled features.”
- A method flow chart from Tesla’s autonomous 3D labeling patent. | Image: Tesla/USPTO
- A method flow chart from Tesla’s Smart Summon patent application. | Image: Tesla/USPTO
The application goes on to describe how labeled training data is made autonomously in their invention using sensors and the collection of what’s called a “time series,” i.e., a series of images captured over a period of time.
“Using data captured by sensors on a vehicle to capture the environment of the vehicle and vehicle operating parameters, a training data set is created,” it explains. “In some embodiments, a three-dimensional representation of a feature, such as a lane line, is created from the group of time series elements that corresponds to the ground truth… As one example, a series of images for a time period, such as 30 seconds, is used to determine the actual path of a vehicle lane line over the time period the vehicle travels…a single image of the group and the actual path taken can be used as training data to predict the path of the vehicle.”
Tesla CEO Elon Musk has previously mentioned that better labeling is one of the keys to speeding up the rollout of self-driving functionality and features like Reverse Summon. “We need to finish work on Autopilot core foundation code & 3D labeling, then functionality will happen quickly. Not long now,” Musk wrote on Twitter in March this year. With better labeling (more accurate training data) comes safer and more capable software due to improved predictions from the modeling.

When it comes to Tesla’s Smart Summon, prediction modeling is essential considering there isn’t a driver in the vehicle during its operation. The patent publication covering Summon embodies the first application’s time series functionality and a second application’s implementation of the time series’ training data in its methods, demonstrating one of the numerous potential uses for the machine learning invention. Hints about future developments using Smart Summon are also detailed in the application. Examples include:
- Syncing the Smart Summon with a calendar so the vehicle “automatically navigates to arrive at the location at the ending time, such as the end of a dinner party, a wedding, a restaurant reservation, etc.”
- Implementing a multi-part destination into the Summon instructions such as waypoints at an airport to pick up multiple passengers.
- Monitoring the heartbeat of a Summon user to ensure they are maintaining a connection with the vehicle while operating the feature.
- Customizing the vehicle’s arrival settings such as interior lighting, exterior lighting, hazard lights, welcome music, and climate control preferences.
One of the more unique bits about the Smart Summon patent application is the appearance of Elon Musk as an inventor. While the CEO is known to be intimately involved in nearly all aspects of vehicle design, software features, and business operations, his name is unexpectedly absent from most of the company’s inventions. However, this is apparently on purpose. “I generally try my best not to be on patents,” he revealed on Twitter in reply to a post about the Smart Summon application. Notably, inventorship is a legal definition based on the conception of an invention, i.e., not the person/people who suggested or directed its creation, but the person/people who devised the means to accomplish it.
Prior to the most recent patent publication, Musk contributed inventorship to the door and body styling of the Model X. He also contributed the same to both the design and function of Tesla’s vehicle charge inlets.
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Tesla FSD V14.2.1 is earning rave reviews from users in diverse conditions
Tesla’s Full Self-Driving (Supervised) software continues its rapid evolution, with the latest V14.2.1 update drawing widespread praise.
Tesla’s Full Self-Driving (Supervised) software continues its rapid evolution, with the latest V14.2.1 update drawing widespread praise for its smoother performance and smarter decision-making.
Videos and firsthand accounts from Tesla owners highlight V14.2.1 as an update that improves navigation responsiveness, sign recognition, and overall fluidity, among other things. Some drivers have even described it as “more alive than ever,” hinting at the system eventually feeling “sentient,” as Elon Musk has predicted.
FSD V14.2.1 first impressions
Early adopters are buzzing about how V14.2.1 feels less intrusive while staying vigilant. In a post shared on X, Tesla owner @LactoseLunatic described the update as a “huge leap forward,” adding that the system remains “incredibly assertive but still safe.”
Another Tesla driver, Devin Olsenn, who logged ~600 km on V14.2.1, reported no safety disengagements, with the car feeling “more alive than ever.” The Tesla owner noted that his wife now defaults to using FSD V14, as the system is already very smooth and refined.
Adverse weather and regulatory zones are testing grounds where V14.2.1 shines, at least according to testers in snow areas. Tesla watcher Sawyer Merritt shared a video of his first snowy drive on unplowed rural roads in New Hampshire, where FSD did great and erred on the side of caution. As per Merritt, FSD V14.2.1 was “extra cautious” but it performed well overall.
Sign recognition and freeway prowess
Sign recognition also seemed to show improvements with FSD V14.2.1. Longtime FSD tester Chuck Cook highlighted a clip from his upcoming first-impressions video, showcasing improved school zone behavior. “I think it read the signs better,” he observed, though in standard mode, it didn’t fully drop to 15 mph within the short timeframe. This nuance points to V14.2.1’s growing awareness of temporal rules, a step toward fewer false positives in dynamic environments.
FSD V14.2.1 also seems to excel in high-stress highway scenarios. Fellow FSD tester @BLKMDL3 posted a video of FSD V14.2.1 managing a multi-lane freeway closure due to a police chase-related accident. “Perfectly handles all lanes of the freeway merging into one,” the Tesla owner noted in his post on X.
FSD V14.2.1 was released on Thanksgiving, much to the pleasant surprise of Tesla owners. The update’s release notes are almost identical to the system’s previous iteration, save for one line item read, “Camera visibility can lead to increased attention monitoring sensitivity.”
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Tesla FSD Supervised ride-alongs in Europe begin in Italy, France, and Germany
The program allows the public to hop in as a non-driving observer to witness FSD navigate urban streets firsthand.
Tesla has kicked off passenger ride-alongs for Full Self-Driving (Supervised) in Italy, France and Germany. The program allows the public to hop in as a non-driving observer to witness FSD navigate urban streets firsthand.
The program, detailed on Tesla’s event pages, arrives ahead of a potential early 2026 Dutch regulatory approval that could unlock a potential EU-wide rollout for FSD.
Hands-Off Demos
Tesla’s ride-along invites participants to “ride along in the passenger seat to experience how it handles real-world traffic & the most stressful parts of daily driving, making the roads safer for all,” as per the company’s announcement on X through its official Tesla Europe & Middle East account.
Sign-ups via localized pages offer free slots through December, with Tesla teams piloting vehicles through city streets, roundabouts and highways.
“Be one of the first to experience Full Self-Driving (Supervised) from the passenger seat. Our team will take you along as a passenger and show you how Full Self-Driving (Supervised) works under real-world road conditions,” Tesla wrote. “Discover how it reacts to live traffic and masters the most stressful parts of driving to make the roads safer for you and others. Come join us to learn how we are moving closer to a fully autonomous future.”
Building trust towards an FSD Unsupervised rollout
Tesla’s FSD (Supervised) ride-alongs could be an effective tool to build trust and get regular car buyers and commuters used to the idea of vehicles driving themselves. By seating riders shotgun, Tesla could provide participants with a front row seat to the bleeding edge of consumer-grade driverless systems.
FSD (Supervised) has already been rolled out to several countries, such as the United States, Canada, Australia, New Zealand, and partially in China. So far, FSD (Supervised) has been received positively by drivers, as it really makes driving tasks and long trips significantly easier and more pleasant.
FSD is a key safety feature as well, which became all too evident when a Tesla driving on FSD was hit by what seemed to be a meteorite in Australia. The vehicle moved safely despite the impact, though the same would likely not be true had the car been driven manually.
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Swedish union rep pissed that Tesla is working around a postal blockade they started
Tesla Sweden is now using dozens of private residences as a way to obtain license plates for its vehicles.
Two years into their postal blockade, Swedish unions are outraged that Tesla is still able to provide its customers’ vehicles with valid plates through various clever workarounds.
Seko chairman Gabriella Lavecchia called it “embarrassing” that the world’s largest EV maker, owned by CEO Elon Musk, refuses to simply roll over and accept the unions’ demands.
Unions shocked Tesla won’t just roll over and surrender
The postal unions’ blockade began in November 2023 when Seko and IF Metall-linked unions stopped all mail to Tesla sites to force a collective agreement. License plates for Tesla vehicles instantly became the perfect pressure point, as noted in a Dagens Arbete report.
Tesla responded by implementing initiatives to work around the blockades. A recent investigation from Arbetet revealed that Tesla Sweden is now using dozens of private residences, including one employee’s parents’ house in Trångsund and a customer-relations staffer’s home in Vårby, as a way to obtain license plates for its vehicles.
Seko chairman Gabriella Lavecchia is not pleased that Tesla Sweden is working around the unions’ efforts yet again. “It is embarrassing that one of the world’s largest car companies, owned by one of the world’s richest people, has sunk this low,” she told the outlet. “Unfortunately, it is completely frivolous that such a large company conducts business in this way.”
Two years on and plates are still being received
The Swedish Transport Agency has confirmed Tesla is still using several different workarounds to overcome the unions’ blockades.
As noted by DA, Tesla Sweden previously used different addresses to receive its license plates. At one point, the electric vehicle maker used addresses for car care shops. Tesla Sweden reportedly used this strategy in Östermalm in Stockholm, as well as in Norrköping and Gothenburg.
Another strategy that Tesla Sweden reportedly implemented involved replacement plates being ordered by private individuals when vehicles change hands from Tesla to car buyers. There have also been cases where the police have reportedly issued temporary plates to Tesla vehicles.


