Tesla's cameras around placed strategically around the vehicle
Tesla
In Tesla's mission to shape the future of sustainable transportation, a pivotal part is played by its camera systems. Designed to enhance safety, enable autonomous features, and provide security against threats, these cameras have evolved significantly over the years.
The Evolution of Tesla's Camera Systems: From MobileEye to Hardware 4
Tesla's journey with integrating cameras into their vehicles started post-2014. The early models with the Autopilot 1 (AP1) system used technology from MobileEye, a leader in Advanced Driver Assistance Systems (ADAS).
However, with the arrival of the Model 3 and Model Y and the 2021 redesigned Model S and Model X, the game changed. All these models now feature nine cameras. Fast forward to 2023, some models are now equipped with Hardware 4.0 (HW4), which have eight higher resolution cameras, and reduce the front-facing cameras to two.
Front Cameras
Teslas have three front-facing cameras with HW3 and two with HW 4
Tesla
The front cameras are located at the top of the windshield. They consist of a camera with a typical lens, a wide-angle lens, and a telephoto lens. The telephoto camera can see up to 250 meters ahead according to Tesla, ideal for high-speed Autopilot use, while the main lens covers 150 meters. In addition, the wide-angle lens gives a panoramic-like view for navigation at complex intersections and tight curves.
Rear View Camera
The rearview camera is positioned above the license plate. It provides a view of up to 50 meters behind the vehicle, assisting with parking, reverse driving and reverse automatic emergency braking.
Fender Cameras
Teslas contain a camera on each fender that points toward the rear of the vehicle at about a 45° angle. This allows the vehicle to see vehicles to its side and help monitor the vehicle's blind spots.
These cameras can also be viewed by the driver when using Tesla's blind spot monitor feature, or by enabling the side cameras while in reverse, which displays the reverse camera feed, along with the fender or 'repeater' cameras.
B-Pillar Cameras
Tesla vehicles also include two other side cameras that are found on the B-pillar. Instead of aiming backward like the repeater cameras, these cameras are aimed toward the front of the vehicle. This allows them to capture areas in the front half of the vehicle. These cameras aid with intersections, parking and more. Unfortunately, the video from these cameras can only be viewed while the vehicle is parked and by going to Controls > Service and tapping on 'Preview Cameras'.
Cabin Camera
All current Tesla models include a cabin camera. The camera is located above the rearview mirror and monitors driver attentiveness, especially when Autopilot is in use. You can view the cabin camera onscreen by navigating to Controls > Service > Preview Cabin Camera. You can also view it through the Tesla app if Sentry Mode is enabled and Sentry Mode Live Access is available in your region.
Future Bumper Camera
Looking ahead, newer Tesla models are expected to feature a bumper camera, as seen in the Cybertruck prototypes. Additionally, with hardware 4.0, the cameras have a higher resolution and an anti-glare coating for enhanced visibility.
Functionality Unveiled: The Multifaceted Uses of Tesla's Cameras
Tesla's cameras play a vital role in the advanced features the vehicles are known for. Their primary use is for the Autopilot system and active safety features like Automatic Emergency Braking (AEB). Furthermore, Sentry Mode and Dashcam features use cameras to record potential threats when parked and on the road. In newer models, the cabin camera monitors driver attentiveness to ensure safety during Autopilot use.
View, Access and Calibrate
Tesla now lets you preview all cameras included in your vehicle
Simon
While driving, you can access the rear and fender cameras through the center display. To test or preview other cameras, you can navigate to Controls > Service > Preview Cameras, and then select the camera you'd like to preview at the top of the screen. In addition, through the Tesla app, remote viewing capabilities are available for five of the vehicle's cameras, including the front-facing camera, fender cameras, rear camera, and cabin camera.
If you're noticing issues with your vehicle's cameras, Tesla provides the ability to calibrate them. It's a simple process initiated from the vehicle's touchscreen, although certain features like Autopilot will be unavailable until the process completes.
Confidentiality in Focus: Tesla's Data Privacy Measures
Tesla takes data privacy seriously. For example, the cabin camera doesn't save or transmit data unless data sharing is enabled in your car's settings. For Sentry Mode and Dashcam footage, data is stored locally and can be accessed only by the owner.
Tesla's advanced camera systems play an integral role in enhancing vehicle safety, providing driver-assist features, and creating a robust security layer. However, understanding the function and usage of these cameras is essential for maximizing the benefits. With Tesla continuously innovating, exciting enhancements, like bumper cameras and upgraded hardware, lie on the horizon, promising to take vehicular safety and autonomy to the next level.
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With Tesla’s first major expansion of the Robotaxi Geofence now complete and operational, they’ve been hard at work with validation in new locations - and some are quite the drive from the current Austin Geofence.
Validation fleet vehicles have been spotted operating in a wider perimeter around the city, from rural roads in the west end to the more complex area closer to the airport. Tesla mentioned during their earnings call that the Robotaxi has already completed 7,000 miles in Austin, and it will expand its area of operation to roughly 10 times what it is now. This lines up with the validation vehicles we’ve been tracking around Austin.
Based on the spread of the new sightings, the potential next geofence could cover a staggering 450 square miles - a tenfold increase from the current service area of roughly 42 square miles. You can check this out in our map below with the sightings we’re tracking.
If Tesla decides to expand into these new areas, it would represent a tenfold increase over their current geofence, matching Tesla’s statement. The new area would cover approximately 10% of the 4,500-square-mile Austin metropolitan area. If Tesla can offer Robotaxi services in that entire area, it would prove they can tackle just about any city in the United States.
From Urban Core to Rural Roads
The locations of the validation vehicles show a clear intent to move beyond the initial urban and suburban core and prepare the Robotaxi service for a much wider range of uses.
In the west, validation fleet vehicles have been spotted as far as Marble Falls - a much more rural environment that features different road types, higher speed limits, and potentially different challenges.
In the south, Tesla has been expanding towards Kyle, which is part of the growing Austin-San Antonio suburban corridor spanning Highway 35. San Antonio is only 80 miles (roughly a 90-minute drive) away, and could easily become part of the existing Robotaxi area if Tesla obtains regulatory approval there.
In the East, we haven’t spotted any new validation vehicles. This is likely because Tesla’s validation vehicles originate from Giga Texas, which is located East of Austin. We won’t really know if Tesla is expanding in this direction until they start pushing past Giga Texas and toward Houston.
Finally, there have been some validation vehicles spotted just North of the new expanded boundaries, meaning that Tesla isn’t done in that direction either. This direction consists of the largest suburban areas of Austin, which have so far not been serviced by any form of autonomous vehicle.
Rapid Scaling
This new, widespread validation effort confirms what we already know. Tesla is pushing for an intensive period of public data gathering and system testing in a new area, right before conducting geofence expansions. The sheer scale of this new validation zone tells us that Tesla isn’t taking this slowly - the next step is going to be a great leap instead, and they essentially confirmed this during this Q&A session on the recent call. The goal is clearly to bring the entire Austin Metropolitan area into the Robotaxi Network.
While the previous expansion showed off just how Tesla can scale the network, this new phase of validation testing is a demonstration of just how fast they can validate and expand their network. The move to validate across rural, suburban, and urban areas simultaneously shows their confidence in these new Robotaxi FSD builds.
Eventually, all these improvements from Robotaxi will make their way to customer FSD builds sometime in Q3 2025, so there is a lot to look forward to.
For years, the progress of Tesla’s FSD has been measured by smoother turns, better lane centering, and more confident unprotected left turns. But as the system matures, a new, more subtle form of intelligence is emerging - one that shifts its attention to the human nuances of navigating roads. A new video posted to X shows the most recent FSD build, V13.2.9, demonstrating this in a remarkable real-world scenario.
Toll Booth Magic
In the video, a Model Y running FSD pulls up to a toll booth and smoothly comes to a stop, allowing the driver to handle payment. The car waits patiently as the driver interacts with the attendant. Then, at the precise moment the toll booth operator finishes the transaction and says “Have a great day”, the vehicle starts moving, proceeding through the booth - all without any input from the driver.
If you notice, there’s no gate here at this toll booth. This interaction all happened naturally with FSD.
While the timing was perfect, the FSD wasn’t listening to the conversation for clues (maybe one day, with Grok?) The reality, as explained by Ashok Elluswamy, Tesla’s VP of AI, is even more impressive.
It can see the transaction happening using the repeater & pillar cameras. Hence FSD proceeds on its own when the transaction is complete 😎
FSD is simply using the cameras on the side of the vehicle to watch the exchange between the driver and attendant. The neural network has been trained on enough data that it can visually recognize the conclusion of a transaction - the exchange of money or a card and the hands pulling away - and understands that this is the trigger to proceed.
The Bigger Picture
This capability is far more significant than just a simple party trick. FSD is gaining the ability to perceive and navigate a world built for humans in the most human-like fashion possible.
If FSD can learn what a completed toll transaction looks like, it’s an example of the countless other complex scenarios it’ll be able to handle in the future. This same visual understanding could be applied to navigating a fast-food drive-thru, interacting with a parking garage attendant, passing through a security checkpoint, or boarding a ferry or vehicle train — all things we thought that would come much later.
These human-focused interactions will eventually become even more useful, as FSD becomes ever more confident in responding to humans on the road, like when a police officer tells a vehicle to go a certain direction, or a construction worker flags you through a site. These are real-world events that happen every day, and it isn’t surprising to see FSD picking up on the subtleties and nuances of human interaction.
This isn’t a pre-programmed feature for a specific toll booth. It is an emergent capability of the end-to-end AI neural nets. By learning from millions of videos across billions of miles, FSD is beginning to build a true contextual understanding of the world. The best part - with a 10x context increase on its way, this understanding will grow rapidly and become far more powerful.
These small, subtle moments of intelligence are the necessary steps to a truly robust autonomous system that can handle the messy, unpredictable nature of human society.
