Tesla entered into the car industry with their first EV, the original Tesla Roadster. It was more of a proof of concept as Tesla had bigger plans. Tesla's plan to enter the automobile market was to build an expensive, electric sports car that would have high margins and prove to the world what EVs could do.
Tesla planned to minimize their effort by focusing only on the electric components of the car, such as the drivetrain and battery. They would try to leverage other parts from existing auto manufacturers such as Lotus.
However, in the end Tesla ended up creating most of the parts themselves. The final Roadster utilized as little as 7% of the same parts as the Lotus Elise.
Tesla to replace cameras on Teslas with AP 2.0
Tesla didn't make the same mistake again. When they manufactured the Model S in 2012 they decided to build the car from the ground up themselves. The original Model S didn't have any driver assist features. It's hard to say whether Autopilot wasn't something Tesla had started developing yet, or whether they planned to start small and add to the car in later years.
In September 2014, Tesla introduced their first version of Autopilot. Tesla built the hardware, but left driver assist software up to MobilEye, a company that still focuses on creating driver assistance systems today.
With the introduction of Autopilot 2.0 in 2016, Tesla decided to ditch MobilEye and take their platform in-house. It was a sudden and messy breakup, but in the end it was the right decision for Tesla. Autopilot 2.0 took several years before catching up to the capabilities of AP 1.
Since the introduction of AP 2.0, Tesla has offered a FSD package. Many features were not available out of the gate, but Tesla has slowly developed more features that fall into their FSD package.
Although many features have come out as part of the package such as lane keeping, lane changing, Navigate on Autopilot, Smart Summon, Autopark and more, Tesla is still developing its true self driving system. The problem has been more difficult to solve than anybody in the industry realized. Tesla is now making great progress with their latest FSD Beta releases.
Since AP 2, Tesla has used different hardware such as cameras and processors, but camera placements have remained the same. Tesla wanted to keep camera placement consistent across their product lines. From the beginning Tesla developed these cameras and processors to be easily swappable when better technology comes along.
AP 2 Cameras to be Swapped
Autopilot 2.0 cameras had a filter that made it able to absorb more light but it reduced colors captured. At the time Tesla thought this trade off would be worth it, but they now realize that it's better to bring the cameras in line with the ones used today. Since the cameras were made to be swappable if needed, Tesla can go in and swap them out for the same cameras that are used today.
Don’t worry, Tesla prepared for this.
The cameras just pop right off and can be replaced with the latest model.
This is exactly what Tesla is doing. Any Tesla that has FSD and AP 2.0, Tesla will be replacing the camera modules with cameras in 2021 vehicles. The FSD computer will also be replaced with the FSD HW 3.0 computer.
Tesla is planning on introducing a HW 4.0 FSD computer with the introduction of the Cybertruck, but this computer is not meant for FSD 3.0 vehicles. Tesla beleives they can achieve FSD on 3.0 hardware, but 4.0 will give them some extra processing power to increase safety even more.
Yeah, although early production cars will need camera upgrades, as well as FSD computer (all included in the price)
The same will be true if Tesla realizes that 4K or wide-angle cameras are needed in the future. These cameras are relatively inexpensive and Tesla can swap out the hardware if needed in order to achieve FSD.
Elon confirmed on Twitter that all vehicles with FSD and AP 2.0 will indeed need to have their cameras replaced in order to get FSD on city streets. The amount of vehicles released with AP 2.0 was relatively small as Tesla soon moved to AP 2.5 roughly a year later.
Elon didn't mention any timeframe on when Tesla will be updating these cars but Tesla may be waiting for Tesla service demand to be reduced. The demand for Tesla service is at an all time high as the world starts to get back to some form of normal and there has been pent up demand for service as people are addressing issues from the past year.
When Tesla gets to updating these vehicles with newer cameras and FSD computers, there will be no cost to owners as the replacement will be completely free.
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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.
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