Tesla Adds Water Shield to Rear Camera for 2025 Model 3 and Model Y

By Karan Singh
Sawyer Merritt/X

Tesla has initiated another minor design revision, this time improving the rear camera on the Model 3 and Model Y. This minor revision adds a protective lip around the camera, providing better shielding against rain, dirt, snow, and general road grime.

The design revision began rolling out for Model Y vehicles from Shanghai first, with the initial vehicles spotted with the revision dated as early as late September 2024. Tesla regularly makes minor design revisions on its vehicles in between model years, in an iterative design process that gradually improves as more and more vehicles are built.

Design Revision

The design revision adds a small shield around the rear camera, including a small lip towards the bottom end. The little lip is likely going to make the biggest difference, as it will help prevent kickback and wash from the tires landing on the camera lens, which can obscure it.

For now, nothing indicates a potential revision including a camera washer—similar to the Cybertruck’s front camera washer. However, given we already know the Model Y Juniper is likely arriving with a front camera, it’ll probably also have a front camera washer.

This lip for the rear camera should be a nice addition, but we’ll have to see just how much of an improvement it provides in the upcoming winter season as the messy, slushy mix arrives in much of the United States and Canada.

3D Printed Accessory

If you’re feeling left out without the new rear camera shield, you’ll soon be able to 3D print and install a similar design. Some entrepreneurial 3D modelers have already started working on making a retrofittable shield for both the HW3 and HW4 rear cameras.

In the meantime, we recommend using ceramic coating on the rear camera to help keep that slush and grime moving when it does hit the camera. A good application of ceramic coating can help prevent buildup on the lens.

Model S and X

For now, we haven’t seen this design revision on more recent Model S and Model X vehicles yet. There were previously rumors of a light refresh for both of the more premium vehicles. However, we haven’t seen any indications of these changes actually seeing the light of day.

Once the refreshes for these two vehicles arrive, we could see more drastic changes. Tesla has also indicated it is waiting to use some of its upcoming new battery cell technology in 2026, so we could be waiting for a while before seeing further updates to the Model S and Model X.

We’ll be looking for both vehicles to receive this design revision. If you spot them, let us know on social media or on our forums.

Tesla Plans Massive 10x Robotaxi Expansion: A Look at the Potential New Area

By Karan Singh
The map above compares Tesla's current geofence with their potential expansion in yellow.
The map above compares Tesla's current geofence with their potential expansion in yellow.
Not a Tesla App

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.

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.

In the map below, the blue icons are sightings of Tesla validation vehicles, while the yellow map area represents their potential expansion. The map overlays Tesla’s phases 1 and 2 and compares them to Waymo’s first two phases. You can toggle each one by tapping the icon at the top left and choosing which geofences you’d like to view.

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.

No Driver Needed: Tesla FSD Stops at Toll, Waits for Driver to Pay and Takes Off Again [VIDEO]

By Karan Singh
@DirtyTesLa on X

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.

How It Really Works

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.

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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