In our continued series exploring Tesla’s patents, we’re taking a look at how Tesla automates data labeling for FSD. This is Tesla patent WO2024073033A1, which outlines a system that could revolutionize how Tesla trains FSD.
We’ll be approaching this article the same way as others in the past, by breaking it down into easily digestible portions.
Training a sophisticated AI model like FSD requires a tremendous amount of data. But all of that data needs to be labeled - and traditionally, this process has been done manually. Human reviewers have to go in and categorize and tag hundreds of thousands of data points across millions of hours of video.
This isn’t just laborious and rote work, it's time consuming, expensive, and prone to human error. The perfect job to hand off to AI.
Tesla’s Automated Solution
Tesla’s patent introduces a model-agnostic system for automated data labeling. Just like their previous patent on the Universal Translator, this will function for any AI model - but FSD is really what it is for.
The system works by leveraging the vast amounts of data collected by Tesla’s fleet to create a 3D model of the environment, which is then automatically used to label new data.
Three Step Process
This process has three steps, so we’ll look at each individually.
High-Precision Mapping
The system starts by creating a highly accurate 3D map of the environment. This involves fusing data from multiple Tesla vehicles equipped with cameras, radar, and other sensors. The map includes detailed information about roads, lane markings, buildings, trees, and other static objects.
It's like creating a digital twin of the real world, and this is exactly the simulation data that Tesla uses to rapidly test FSD. The system continuously improves its accuracy as it processes more data and also generates better synthetic data to augment the training dataset.
Multi-Trip Reconstruction
To refine the 3D model and capture dynamic elements of the environment, the system analyzes data from multiple trips through the same area. This allows it to identify moving objects, track their trajectories, and understand how they interact with the static environment. This way, you have a dynamic, living 3D world that also captures the ebb and flow of traffic and pedestrians.
Automated Labelling
Once the 3D model is sufficiently detailed, it becomes the key to automated labeling. When a Tesla vehicle encounters a new scene, the system compares the real-time sensor data with the existing 3D model. This allows it to automatically identify and label objects, lane markings, and other relevant features in the new data.
Benefits
There are three simple benefits to this system, which is what makes it so valuable.
It is far more efficient. Automated data labeling drastically reduces the time and resources required to prepare training data for AI models. This accelerates development cycles and allows Tesla to train its AI on much larger datasets.
It is also scalable. This system can handle massive datasets derived from millions of miles of driving data collected by Tesla's fleet. As the fleet grows and collects more data, the 3D models become even more detailed and accurate, further improving the automated labeling process.
Finally, it is accurate. By eliminating human error and bias, automated labeling improves the accuracy and consistency of the labeled data. This leads to more robust and reliable AI models. Of course, human review is still involved, but that’s only to catch and flag errors.
Applications
While this technology has significant implications for FSD, Tesla can use this automated labeling system to train AI models for various tasks.
Object detection and classification: Accurately identifying and categorizing objects in the environment, such as vehicles, pedestrians, traffic signs, and obstacles.
Kinematic analysis: Understanding the motion and behavior of objects, predicting their trajectories, and anticipating potential hazards.
Shape analysis: Recognizing the shapes and structures of objects, even when partially obscured or viewed from different angles.
Occupancy and surface detection: Creating detailed maps of the environment, identifying occupied and free space, and understanding the properties of different surfaces (e.g., road, sidewalk, grass).
These different applications are all used by Tesla - which uses different AI subnets to analyze all these different things before feeding them into the greater model that is FSD, which means things like pedestrians, lane markings, and traffic controls are all labeled on-vehicle.
In a Nutshell
Tesla's automated data labeling system is a game-changer for AI development. By leveraging the power of its fleet and 3D mapping technology, Tesla has created a self-learning system that continuously improves its ability to understand and navigate the world.
Imagine a world where self-driving cars can label and understand the world around them without human help. This patent describes a system that could make that possible. It uses data collected from many Tesla vehicles to create a 3D model of the environment, which is like a virtual copy of the real world.
This 3D model is then used to label new images and sensor data, eliminating most needs for human intervention. The system can recognize objects, lane markings, and other important features, making it easier to train AI models.
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While Tesla’s Cybertruck has access to FSD v13, it still doesn’t include some of the FSD features that are available on other HW4 vehicles. Features such as Start FSD from Park are currently not available on the Cybertruck.
Trusted sources have now informed Not a Tesla App that the Cybertruck will soon receive an FSD update that will enable a series of new features and bring the Cybertruck up to speed with other vehicles. The update is expected to arrive within the next 14 days.
Tesla’s AI team has been relatively quiet recently, and we haven’t seen a major FSD update since FSD v13.2.8 was released on February 17th, but we’re finally getting hints of what’s around the corner.
Here’s our exclusive look at what’s coming in the latest FSD update for Cybertruck.
New Features
If you don’t own a Cybertruck - or even if you do - you may not know that the Cybertruck is missing several FSD-related features. The first three features are all related to parking lot use and Tesla’s low-speed FSD stack, which hasn’t been available on the Cybertruck so far.
This FSD update will add the following features:
Start FSD from Park: Tesla’s Unpark feature allows FSD can be started while the vehicle is still in park. To do so, one can simply set their destination from the navigation and then tap and hold the blue Start FSD button. The car will shift out of park and into drive or reverse to get going.
Since FSD V13.2.1, Start FSD from Park now requires you to also tap the brake while holding down the Start FSD button to prevent accidental activation. This safeguard can be disabled in settings.
Ability to Reverse: FSD previously demonstrated quite a want to reverse - but it was never allowed to. You can tell the planner plans for the vehicle to go into reverse to follow the path, but once the vehicle needs to shift into reverse, it’s blocked from doing so. The Cybertruck will finally be able to shift into reverse - and also seamlessly shift between Park, Drive, and Reverse all by itself. This functionality also enables 3-point turns to help navigate tight spaces.
FSD can now do multi-point turns, even in super-tight locations like parking garages.
Park: Finally, when you arrive at your destination, FSD will now park itself if it finds an open spot near or at the final location. Previously, the user had to initiate Autopark - now, FSD will either switch over to Autopark to back in or park facing front-in based on the parking spot.
Tesla has indicated that new parking features will arrive in a future update that will allow the user to pick whether the vehicle pulls over, parks in a spot, or parks in a driveway or garage when it arrives at the destination.
Improved Controller
While the new features like Start FSD from Park are eye-catching, this improved controller will actually be the largest improvement to this FSD update.
This upcoming update improves FSD’s traffic control process, improving prediction accuracy, position tracking in 3D space, and environmental analysis. These changes allow FSD to make faster decisions, anticipate turns and lane changes sooner, and operate more smoothly.
The difference between FSD V12 and V13 had a major impact on driving feel and smoothness, but these improvements were never fully reached with the Cybertruck. While smoothness improved, it wasn’t on par with Tesla’s other HW4 models—until now.
Actually Smart Summon
The final part of the update is probably going to be the most fun - the arrival of Actually Smart Summon. This feature was launched back in September 2024 for other Tesla vehicles, but it was nowhere in sight for the Cybertruck.
We initially chalked this up to Tesla needing more time to improve and work on testing the Cybertruck’s vision accuracy with their LiDAR testing rigs. However, it really does seem like Tesla has been holding off on this update for quite some time to integrate the front bumper camera into Actually Smart Summon.
With Actually Smart Summon, other Tesla vehicles will sometimes roll backward in their parking spots - to ensure that nothing is up against the front bumper. This can make Actually Smart Summon unavailable when you’re parked too close to a wall, as the car doesn’t see what’s between the edge of the hood and the ground.
The front bumper camera is Tesla’s solution to this problem. The Cybertruck and the Refreshed Model Y are both equipped with a new camera in the front bumper, enabling them to see perfectly in this blind spot. At low speeds, the camera is extremely useful, providing excellent coverage of a zone of the vehicle that is generally difficult to see for drivers - and impossible for the primary camera cluster.
Update Release Date
This FSD update will be massive for Cybertruck owners as it’ll finally bring the latest FSD features and improvements to the electric truck.
From the very beginning, Tesla chose to use its own proprietary Linux-based operating system instead of relying heavily on CarPlay and Android Auto. This also meant that it had to develop its own mapping solution that would live at the center of its infotainment space.
These maps would need to seamlessly integrate with the vehicle to plan energy-efficient routes and dynamically adjust navigation based on the battery’s state of charge.
Tesla currently uses Google Maps for most of the underlying features of its Maps app for most of the world, with Baidu Maps data being leveraged in China. Some of the map data, such as street data and voice navigation, are preloaded and updated regularly. MapBox, another software provider that has been working on these projects for over a decade, supplies the routing engine.
Navigation Routing
In 2018, MapBox purchased the 'Valhalla' routing engine, which is now part of the core API MapBox provides to users and enterprise clients like Tesla. Valhalla includes features like expanded guidance with clear and concise instructions along the route, as well as turn restrictions, highway exit information, and time zones. Although Tesla relies on Google Map APIs to build out most of their navigation app, the routing is done on Tesla’s servers using Valhalla.
Some map features, such as live traffic visualization and satellite view, require a subscription to Tesla’s Premium Connectivity data plan to access; however, a vehicle with standard connectivity will still have access to traffic-based routing, the Trip Planner, and Supercharger stall availability.
Map Updates
Tesla releases new navigation maps about twice per year, but there is no hard rule. If the version of your maps is more than a year old, you may need to connect to WiFi to download the latest updates. Not having the latest map version could prevent certain features, such as FSD, from working. If you’re not able to connect to WiFi at home, you can try a Tesla Service Center, some Supercharger locations, or a local business that has WiFi access outside.
Keep in mind that map updates are several gigabytes in size and could take a considerable amount of time to download.
Map downloads are similar to software updates in that they are rolled out gradually and not everyone will have access to the latest version right away.
Unlike software updates, map updates are downloaded silently in the background when your vehicle is connected to WiFi, so you may not even be aware that your vehicle received newer navigation data.
What’s in a Map Update
Tesla uses a combination of streamed data and map data to display what you see on your navigation screen. The navigation data that is downloaded separately includes street-level data, speed limits, points of interest (business locations), and more.
While other data is actually streamed on request and you receive the latest version when you request it. This includes the navigation tiles or images, which are what you see visually on the navigation app. Routing is also computed on Tesla’s servers instead of in the vehicle if you have that option enabled under Controls > Navigation.
How to Check for a Map Update
On your car’s touchscreen, you can go to Controls > Software to see whether there is a map update available for your vehicle. Scroll down to Navigation Data, and your current map version will be listed underneath. It’ll look something like NA-2025.2-12345.
The navigation version consists of the region abbreviation, such as NA or EU, followed by the year and week number when the map data was created. The last five digits are the build number of the map data.
If your car is ready to download a map update but isn't connected to Wi-Fi, a download progress bar will appear, similar to a vehicle update. However, to download the most recent Tesla maps, your car must be connected to Wi-Fi.
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