The Tesla Model S competes against other EVs like VW's ID.Buzz to find out which vehicle can travel the furthest in extreme conditions
Motor.no
The Northern tundra of Norway played host to an electrifying showdown as Motor Magazine pitted the latest and greatest electric vehicles against each other in a grueling test of winter endurance. With bone-chilling temperatures, only the bravest and most efficient cars could cross the finish line. However, the Tesla Model S was the clear winner when the dust and snowflakes settled.
This sleek electric sedan not only braved the frigid temperatures but also shattered the previous winter range record, reaching a whopping 530 kilometers (329 miles) on a single charge. While other vehicles struggled to maintain their range, the Model S powered on, proving once and for all that electric cars can handle anything Mother Nature throws their way. It's worth mentioning that the Model S had a slight disadvantage from the get-go - due to a technical issue, the battery could only be charged to 98%.
How the Rest of the Field Fared
As expected, the harsh winter weather took a toll on the other cars in the test. Most cars stopped much earlier than expected, but the Model S saw one of the lowest range deviations at just 16%. The Model X Plaid was second with 444 kilometers (276 miles) and an 18% deviation. Meanwhile, the Toyota bZ4X had the most considerable discrepancy, with a deviation of over 35% and just 323 kilometers (201 miles) driven. Oddly enough, Toyota did not provide its all-wheel drive version of the bZ4X. Subaru's Solterra, the twin to the bZ4X, also did not offer an all-wheel drive edition.
China Emerges as the Driving Force in the Electric Car Industry
The winter range test also saw a significant number of cars from China, with 12 of the test cars hailing from the country. From the affordable MG4 and BYD Atto to the luxury SUV Voyah Free, Chinese electric cars are making a big splash in the industry. These cars prove development in the electric car industry is moving fast, and China is at the forefront.
Winter is no friend to electric cars. Electric heaters and heat pumps work overtime, snow drifts make the roads unpredictable, and drivers are left counting down the miles until they need to reach a charging station. This test provides a real-world look at how electric cars perform in harsh winter weather, and it's clear that the Tesla Model S is one of the best in the business.
Subscribe
Subscribe to our newsletter to stay up to date on the latest Tesla news, upcoming features and software updates.
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.
![No Driver Needed: Tesla FSD Stops at Toll, Waits for Driver to Pay and Takes Off Again [VIDEO]](https://www.notateslaapp.com/img/containers/article_images/fsd-beta/fsd-toll-booth.webp/57e008aff60c6c1e998e304eca200cda/fsd-toll-booth.jpg)
_300w.png)
