Supercharging is fast and convenient, but there are times when a station reaches full capacity, requiring drivers to wait for an available stall. When there are only a few vehicles in line, the wait is minimal, and figuring out whose turn it is to charge is straightforward. However, long queues can form during peak travel times or in high-traffic areas, leading to confusion and frustration as vehicles cut the line.
Currently, there is no official system for managing Supercharger queues—drivers rely on informal, self-organized lines. While many follow an unspoken order, disputes can arise when some claim they arrived first or attempt to cut ahead.
Urban Superchargers in cities like Toronto, Los Angeles, and New York often see long lines during busy hours, with drivers doing their best to maintain order. A structured queuing system could help streamline the process, reducing conflicts and ensuring a fair, organized charging experience for all, and that’s exactly what Tesla is about to implement.
Virtual Queue
The Tesla Charging account on X has confirmed that it plans to introduce a Virtual Queuing system, with a pilot program set to launch at select Supercharger sites next quarter. While Tesla has yet to specify which locations will be included, it’s likely the initial rollout will take place in the United States, where the company typically begins testing new charging initiatives.
Tesla says that if the pilot program receives positive feedback, they will expand the system to more Superchargers this year.
The goal of Virtual Queuing is to improve the charging experience whenever wait times occur. According to Tesla, this would apply to roughly “~1% of cases,” though many high-demand Supercharger sites frequently experience long lines. While some remote locations may see little to no wait times, busier stations could greatly benefit from a structured queuing system.
Potential Implementations
While Tesla hasn’t detailed exactly how the Virtual Queuing system will work, there are a few likely possibilities. One approach could involve locking a vehicle’s VIN into the queue, preventing other vehicles from starting a charge prematurely. In this case, any attempt to charge out of turn might trigger a “Stall reserved for next vehicle in line” message.
This method would provide a straightforward solution—only the next vehicle in the queue would be able to initiate a session. The queuing process itself could be automated when a vehicle navigates to the Supercharger, factoring in estimated arrival time, or it might require manual enrollment once you arrive.
Tesla may also impose limits on queue validity. If a vehicle leaves the charging area, its position could be automatically forfeited.
Software Solution
In China, Superchargers sometimes include locks that come up from the ground, preventing non-Teslas from parking in these designated Supercharger spots. Up until recently, Tesla users had to open up the Tesla app and choose a stall before the lock would go down and allow them to park. However, with a recent update, this is all done on the vehicle’s screen, where the driver can pick the charging stall and automatically have the lock lower.
We may see a similar implementation, where a driver would choose to add themselves to the Supercharger queue, and their position in line and estimated wait time would then be viewable on the vehicle’s screen.
Reservation Signage
Tesla’s reservation about this new queuing system could be around driver confusion. Superchargers weren’t built with a queue system in mind, meaning that there’s no way to tell whether a stall is reserved for a specific vehicle.
A physical indicator could help owners quickly identify when a Supercharger stall is available for the next vehicle in the queue. Tesla could implement a system similar to grocery store checkout lights, where a change in lighting signals whether a register is open or closed.
For example, the Supercharger post could pulse blue when it’s ready for the next user, with a corresponding message in the vehicle stating, “Use the Supercharger post that is pulsing blue.” This would provide a clear, intuitive way to direct drivers to the correct stall.
Tesla can also display a menu inside a vehicle when it first arrives at a Supercharger, letting the driver know that there’s a wait time and explaining the process and their estimated wait time. It can also prompt the driver to be added to the queue.
Tesla Priority
Another factor to consider is how Tesla will handle non-Tesla vehicles in the queue. One possibility is giving priority access to Tesla owners or those subscribed to the Supercharger membership. This would ensure that Tesla vehicles and paying members receive preferred access at busy Supercharger sites, making the membership more valuable while also incentivizing Tesla ownership—especially as the network expands to other EV brands.
Regardless of whether Tesla introduces priority access, the Supercharger queuing system will be a valuable addition, particularly in high-traffic urban locations and during peak travel seasons. By having an official queue Tesla will create a smoother and more organized charging experience for all users.
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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.
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.