Tesla's software and monthly updates makes for a unique experience
My Tesla Model 3, unimaginatively named "Blue Tesla," is relatively new. I bought it in June 2020 during the pandemic. Didn't really need it. Not going many places. Bought it anyway. I'd been thinking about buying one for a long time.
Because it was a pandemic, they arranged a touchless buying experience. They called me from the Tesla place when the car arrived. They said it was the blue Model 3 outside the door of the showroom. It just so happens that I live relatively near the Tesla Service Center in Owings Mills, Maryland It looks more like a regular car dealership than most of the Tesla stores.
So I went there, and I couldn't figure out how to get into the car. Remember touchless? Well, there wasn't even a salesperson around. I had gone on a test drive a few months previously, before the pandemic. The salesperson had opened the door for me. I remembered that the model S has a handle that comes out to greet you when you put your hand near it. Not the Model 3. After poking and prodding a bit, I called the number they gave me and spoke to someone inside the showroom. He pointed out that if I pressed in on the back of the handle with my thumb, the front part of the handle will swivel out from the door, and I could grab it with my fingers. It's nice that the handles are flush with the doors. Less drag and less wind noise when driving at highway speeds. But people unfamiliar with the Model 3, including some of the Model S and X owners, won't be able to open the doors of your Model 3.
Then, I sat in the car and signed the papers. I put the papers and the check in the envelope and put it in the slot in the door of the showroom. I gotta say, this was the quickest car buying experience I've ever had, and I've been driving for sixty years. On the other hand, this car has lots of differences, and I didn't get an orientation. Fortunately, YouTube has the orientation. Here's a link to one of them.
Shifting is a bit different than most other cars. The shift lever goes back to a neutral position when you shift so you need to use other cues to know what gear you're in. I was used to this because I used to drive a Prius, and they have the same issue. Here are the clues.
If you're in Park, the picture of your car on the center screen is seen from the left front. The picture of your car, with its original color, is angled towards the left lower corner of the screen. Push down on the steering column mounted gearshift lever for Drive and up for Reverse.
In Reverse, the picture of the car is seen from the top, and you get a big picture from your backup camera with lines showing you where the car is going to go if you back up. That's a really good clue that you're in Reverse gear. Turn the steering wheel, and the lines move.
If you're in drive, the car is pictured as if you're looking at the car from the rear and slightly above. You can see that the car is going to go forward. If you're going less than five mph such as backing out of your driveway, you don't need to stop before shifting to Drive. You don't even need to step on the brake. Just shift to Drive, and the electric motor will stop the car and immediately start it going forward.
That will get you on the road. There are lots of helpful videos on YouTube about the features of the Model 3. Those videos are an excellent way to learn about your new car. Go to YouTube and search on Tesla Model 3.
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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.
