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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.
Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.
Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.
Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.
These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.
READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.
For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.
🚨 Tesla Full Self-Driving v14.3 proceeds through an Except Right Turn Stop Sign pic.twitter.com/YemRSlens7
— TESLARATI (@Teslarati) April 8, 2026
That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.
This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.
Florida Governor Ron DeSantis has sharply criticized legacy media outlets for what he describes as selective and biased reporting on vehicle accidents involving Tesla. In a recent X post, DeSantis questioned why headlines routinely spotlight the Tesla brand in crash stories, even when human error is the clear cause, while similar incidents with other automakers often receive generic treatment.
A prime example is the June 19, 2026, fatal crash in Katy, Texas. A Tesla Model 3 driven by Michael Butler struck a brick home at high speed, killing 76-year-old Martha Avila inside. Initial reports and headlines prominently featured “Tesla crash” and referenced the driver’s claim that an automated driving-assistance system was engaged.
Many outlets quickly speculated that Full Self-Driving or Autopilot were the cause of the crash, immediately blaming the suites for the accident shortly after it happened.
However, Tesla responded shortly after the accident with vehicle data that showed Butler manually overrode the system by pressing the accelerator to 100 percent, reaching 73 MPH in a residential area, more than double the speed limit. The accelerator remained floored after impact.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
The National Transportation Safety Board (NTSB) later confirmed these findings, and Butler now faces manslaughter charges. His phone searches also included queries like “Tesla FSD too timid,” suggesting he may have intervened aggressively. Despite this, many headlines continued to center Tesla’s technology rather than the driver’s actions.
DeSantis highlighted a Washington Post headline, which was labeled, “Newly released photo shows wreckage of Tesla crash that killed grandmother.”
Do legacy media outlets typically use headlines involving the make of a car in a crash or is that only for Tesla?
It would be one thing if the self-driving malfunctioned but the crash was purely human-induced.
Seems like these outlets want to associate Tesla with crashes as… pic.twitter.com/EmfyeYiuv6
— Ron DeSantis (@RonDeSantis) July 17, 2026
The subheadline noted the driver overrode assistance and floored the accelerator, yet the brand name dominated the framing. He asked whether legacy outlets typically name the make of a car in routine crashes or reserve that treatment for Tesla to push a narrative.
This pattern appears widespread. Crashes involving Ford, Chevrolet, or Toyota vehicles frequently appear as “pickup truck slams into home” or “fatal car crash kills pedestrian” without brand specifics, especially absent new technology angles.
High-profile Ford F-150 or Chevy Silverado incidents tied to large sales volumes often escape brand-callout scrutiny. In contrast, Tesla stories consistently lead with the manufacturer, amplifying perceptions of risk despite data showing strong overall safety performance:
🚨 Why do Tesla Owners get so defensive over the narrative of crashes involving Teslas? https://t.co/aX7ogtjTCR pic.twitter.com/KO4QWaLOKl
— TESLARATI (@Teslarati) June 24, 2026
Tesla’s own 2025 Impact Report indicates vehicles using FSD logged 0.19 major incidents per million miles, roughly eight times fewer than the U.S. average. Models like the Model Y also rank among the safest in IIHS and NHTSA testing for occupant protection. Critics argue disproportionate coverage ignores these statistics and driver behavior factors, such as younger or more aggressive Tesla owners in some studies.
DeSantis frames this as part of a broader political agenda against innovative American companies like Tesla. By consistently naming Tesla while downplaying others, media outlets risk eroding public trust and shaping perceptions detached from the evidence of human error in most cases.
As autonomous technology evolves across the industry, consistent and factual reporting will be essential to separate real safety concerns from narrative-driven coverage.
Tesla entered two new markets this week by advancing its presence in Latvia (Europe) and officially launching operations in Uruguay (South America), marking a rapid dual-continent expansion.
These moves underscore the company’s strategy to tap into emerging EV markets with supportive policies, renewable energy grids, and growing demand for sustainable transport.
Latvia: Strengthening the Baltic Footprint
In Latvia, Tesla has built on its earlier registration of Tesla Latvia SIA in late 2025 with recent steps toward full operations, including job postings for a service center and representation in Riga. This aligns with broader Baltic expansion following Lithuania’s model of pop-up stores and service centers.
Coming to Latvia https://t.co/XNkQQJ2O6a pic.twitter.com/yS9kpcNky1
— Tesla Europe, Middle East & Africa (@teslaeurope) July 17, 2026
EV penetration in Latvia stands at around 7 percent for BEVs in new passenger car registrations. 2025 data showed 1,602 BEVs out of about 22,500 total, or 7.1 percent, with combined plug-ins nearing 19 percent. Growth has been steady but below the European average, supported by government subsidies and infrastructure development. Tesla models like the Model 3 lead local EV registrations.
Vehicles for the Latvian market will likely be sourced from Gigafactory Berlin or Gigafactory Shanghai. Charging infrastructure is robust for the region as well, with over 400- 2,000 public points, with Tesla Superchargers in Riga, Jūrmala, and along Via Baltica routes offering up to 250 kW.
Uruguay: Third South American Country
Tesla teased its Uruguay arrival with “Estamos llegando,” or, “We are arriving,” on social media, followed by an official presentation scheduled for mid-July.
Hola Uruguay 🇺🇾
Nuestros Model 3 y Model Y están cada vez mas cerca! pic.twitter.com/FR41fsA7um
— Tesla Latinoamérica (@Tesla_LatAm) June 30, 2026
The company established Tesla Uruguay SAS, homologated Model 3 and Model Y (three versions each), and appointed local leadership. This makes Uruguay Tesla’s third official South American market after Chile and Colombia.
Uruguay boasts one of Latin America’s highest EV penetrations, with battery-electric vehicles exceeding 20 percent market share recently, driven by tax incentives, high fuel prices, and a nearly 95-100 percent renewable electricity grid. Hundreds of Teslas already operate via grey imports, but official sales bring warranties, service, and support.
Vehicles will be imported from Gigafactory Shanghai, enabling competitive pricing for Model 3 and Model Y. Charging plans include Supercharger development alongside existing infrastructure, leveraging the country’s green energy advantage for affordable operation.
Tesla Superchargers follow Model 3 and Model Y to South American country
Tesla’s Dual Continent Expansion
Tesla’s simultaneous push into Latvia and Uruguay demonstrates efficient scaling: prioritizing service and infrastructure first, then direct sales in high-potential niches. In Europe, it fills Baltic gaps; in Latin America, it counters Chinese dominance while leveraging renewables.
This dual move signals Tesla’s ambition to accelerate global EV adoption amid varying regional paces. By addressing local needs, like subsidies in Latvia or incentives and green grids in Uruguay, Tesla not only boosts volumes but advances its mission of sustainable energy.
For investors and consumers, it highlights resilience and opportunity in diverse markets, potentially paving the way for further growth in underserved regions. With strong fundamentals in both, these entries could yield long-term gains as EV transitions mature worldwide.
Elon Musk says your Tesla will start to learn your individual preferences
Ron DeSantis calls out media bias in Tesla crash coverage
