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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.”
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- A method flow chart from Tesla’s autonomous 3D labeling patent. | Image: Tesla/USPTO
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- 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 Model 3 named New Zealand’s best passenger car of 2025
Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.
The refreshed Tesla Model 3 has won the DRIVEN Car Guide AA Insurance NZ Car of the Year 2025 award in the Passenger Car category, beating all traditional and electric rivals.
Judges praised the all-electric sedan’s driving dynamics, value-packed EV tech, and the game-changing addition of Full Self-Driving (Supervised) that went live in New Zealand this September.
Why the Model 3 clinched the crown
DRIVEN admitted they were late to the “Highland” party because the updated sedan arrived in New Zealand as a 2024 model, just before the new Model Y stole the headlines. Yet two things forced a re-evaluation this year.
First, experiencing the new Model Y reminded testers how many big upgrades originated in the Model 3, such as the smoother ride, quieter cabin, ventilated seats, rear touchscreen, and stalk-less minimalist interior. Second, and far more importantly, Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.
FSD changes everything for Kiwi buyers
The publication called the entry-level rear-wheel-drive version “good to drive and represents a lot of EV technology for the money,” but highlighted that FSD elevates it into another league. “Make no mistake, despite the ‘Supervised’ bit in the name that requires you to remain ready to take control, it’s autonomous and very capable in some surprisingly tricky scenarios,” the review stated.
-->At NZ$11,400, FSD is far from cheap, but Tesla also offers FSD (Supervised) on a $159 monthly subscription, making the tech accessible without the full upfront investment. That’s a game-changer, as it allows users to access the company’s most advanced system without forking over a huge amount of money.
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Tesla starts rolling out FSD V14.2.1 to AI4 vehicles including Cybertruck
FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out.
It appears that the Tesla AI team burned the midnight oil, allowing them to release FSD V14.2.1 on Thanksgiving. The update has been reported by Tesla owners with AI4 vehicles, as well as Cybertruck owners.
For the Tesla AI team, at least, it appears that work really does not stop.
FSD V14.2.1
Initial posts about FSD V14.2.1 were shared by Tesla owners on social media platform X. As per the Tesla owners, V14.2.1 appears to be a point update that’s designed to polish the features and capacities that have been available in FSD V14. A look at the release notes for FSD V14.2.1, however, shows that an extra line has been added.
“Camera visibility can lead to increased attention monitoring sensitivity.”
Whether this could lead to more drivers being alerted to pay attention to the roads more remains to be seen. This would likely become evident as soon as the first batch of videos from Tesla owners who received V14.21 start sharing their first drive impressions of the update. Despite the update being released on Thanksgiving, it would not be surprising if first impressions videos of FSD V14.2.1 are shared today, just the same.
-->Rapid FSD releases
What is rather interesting and impressive is the fact that FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out. This bodes well for Tesla’s FSD users, especially since CEO Elon Musk has stated in the past that the V14.2 series will be for “widespread use.”
FSD V14 has so far received numerous positive reviews from Tesla owners, with numerous drivers noting that the system now drives better than most human drivers because it is cautious, confident, and considerate at the same time. The only question now, really, is if the V14.2 series does make it to the company’s wide FSD fleet, which is still populated by numerous HW3 vehicles.
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Waymo rider data hints that Tesla’s Cybercab strategy might be the smartest, after all
These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.
Toyota Connected Europe designer Karim Dia Toubajie has highlighted a particular trend that became evident in Waymo’s Q3 2025 occupancy stats. As it turned out, 90% of the trips taken by the driverless taxis carried two or fewer passengers.
These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.
Toyota designer observes a trend
Karim Dia Toubajie, Lead Product Designer (Sustainable Mobility) at Toyota Connected Europe, analyzed Waymo’s latest California Public Utilities Commission filings and posted the results on LinkedIn this week.
“90% of robotaxi trips have 2 or less passengers, so why are we using 5-seater vehicles?” Toubajie asked. He continued: “90% of trips have 2 or less people, 75% of trips have 1 or less people.” He accompanied his comments with a graphic showing Waymo’s occupancy rates, which showed 71% of trips having one passenger, 15% of trips having two passengers, 6% of trips having three passengers, 5% of trips having zero passengers, and only 3% of trips having four passengers.
The data excludes operational trips like depot runs or charging, though Toubajie pointed out that most of the time, Waymo’s massive self-driving taxis are really just transporting 1 or 2 people, at times even no passengers at all. “This means that most of the time, the vehicle being used significantly outweighs the needs of the trip,” the Toyota designer wrote in his post.
-->Cybercab suddenly looks perfectly sized
Toubajie gave a nod to Tesla’s approach. “The Tesla Cybercab announced in 2024, is a 2-seater robotaxi with a 50kWh battery but I still believe this is on the larger side of what’s required for most trips,” he wrote.
With Waymo’s own numbers now proving 90% of demand fits two seats or fewer, the wheel-less, lidar-free Cybercab now looks like the smartest play in the room. The Cybercab is designed to be easy to produce, with CEO Elon Musk commenting that its product line would resemble a consumer electronics factory more than an automotive plant. This means that the Cybercab could saturate the roads quickly once it is deployed.
While the Cybercab will likely take the lion’s share of Tesla’s ride-hailing passengers, the Model 3 sedan and Model Y crossover would be perfect for the remaining 9% of riders who require larger vehicles. This should be easy to implement for Tesla, as the Model Y and Model 3 are both mass-market vehicles.
Tesla Model 3 named New Zealand’s best passenger car of 2025
Tesla starts rolling out FSD V14.2.1 to AI4 vehicles including Cybertruck
