Tesla has introduced an OEM air mattress, now available in the North American Tesla store. The air mattress retails for $225 USD / $310 CAD.
The air mattress is currently only available in the North American store, and there is no indication when it will be released internationally at this time. Instructions are provided in all international languages and regions Tesla sells cars in, so it could be coming to other regions shortly.
Design
The air mattress is designed to fit within the lower trunk of the Model Y and is adapted to fit exactly within the Model Y’s rear half when the seats are folded down. The mattress will work with either the 5-seat or 7-seat config, as the 7-seater Model Y seats fold down fully flat.
Tesla includes the air mattress with a carry bag, an air pump and an adapter, as well as a pair of repair patches. The air pump plugs into a standard 12V cigarette lighter-style plug. You can find a 12V plug on the left rear side of the vehicle, near the trunk, and above the side-trunk storage.
Material
The folded up Model Y Air Mattress, in the sub-trunk.
Not a Tesla App
The mattress itself is a mix of foam and polyester. The foam is a high-density foam, covering the top 3 inches of the mattress. The entire mattress is wrapped in waterproof polyester, which should make it excellent for camping.
The included carry bag appears to be made of durable canvas material and includes a pair of straps for carrying. It’s the perfect size to fit comfortably within the under-trunk rear storage and should be easy to pack when planning trips.
Update: The mattress is now sold out, but you can sign up to be reminded over email when it becomes available again.
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Tesla has always embraced whimsy in its software, packing it with playful Easter eggs and surprises. From transforming the on-screen car into James Bond’s submarine to the ever-entertaining Emissions Testing Mode and the fan-favorite Rainbow Road, these hidden features have become a signature part of Tesla’s software.
Of course, launching a new product like Robotaxi wouldn’t be complete without a fun little easter egg of its own. The end-of-ride screen in the Robotaxi app presents a familiar option “Leave a tip.”
For anyone pleased with their Robotaxi ride, they may be tempted to leave a tip. However, tapping the button presents our favorite hedgehog instead of a payment screen.
The app displays a message, alongside the familiar Tesla hedgehog, that simply states “Just kidding.”
While it's a fun prank, it’s also a nod to what Tesla really wants to do. They want to reinforce the economic advantage of an autonomous Robotaxi Network. Without a driver, there is simply no need to tip. The gesture is playful, but it’s a reminder of what Tesla’s real aim is here.
Over the last few days, we’ve seen some exceptionally smooth performance from the latest version of FSD on Tesla’s Robotaxi Network pilot. However, the entire purpose of an early access program with Safety Monitors is to identify and learn from edge cases.
This week, the public saw the first recorded instance of a Safety Monitor intervention, providing a first look at how they’re expected to stop the vehicle.
The event involved a complex, low-speed interaction with a reversing UPS truck. The Safety Monitor intervened to stop the Robotaxi immediately, potentially avoiding a collision with the delivery truck. Let’s break down this textbook case of real-world unpredictability.
The Intervention [VIDEO]
In a video from a ride in Austin, a Robotaxi is preparing to pull over to its destination on the right side of the road, with its turn signal active. Ahead, a UPS truck comes to a stop. As the Model Y begins turning into the spot, the UPS truck, seemingly without signaling, starts to reverse. At this point, the Safety Monitor stepped in and pressed the In Lane Stop button on the main display, bringing the Robotaxi to an immediate halt.
This is precisely why Tesla has employed Safety Monitors in this initial pilot. They are there to proactively manage ambiguous situations where the intentions of other drivers are unclear. The system worked as designed, but it raises a key question: What would FSD have done on its own? It’s not clear whether the vehicle saw the truck backing up, or what it would do when it finally detected it. It’s also unclear whether the UPS driver recognized that the Robotaxi was pulling into the same spot at the exact same time.
It’s possible this wouldn’t result in a collision at all, but the Safety Monitor did the right thing by stepping in to prevent a potential collision, even one at low speed. Any collision just a few days after the Robotaxi Network launch could result in complications for Tesla.
Who Would Be At Fault?
This scenario is a classic edge case. It involves unclear right-of-way and unpredictable human behavior. Even for human drivers, the right-of-way here is complicated. While a reversing vehicle often bears responsibility, a forward-moving vehicle must also take precautions to avoid a collision. This legal and practical gray area is what makes these scenarios so challenging for AI to navigate.
Would the Robotaxi have continued, assuming the reversing truck would stop?
Or would it have identified the potential conflict and used its own ability to stop and reverse?
Without the intervention, it’s impossible to say for sure. However, crucial context comes from a different clip involving, surprisingly, another UPS delivery truck.
A Tale of Two Trucks
In a separate video posted on X, another Robotaxi encounters a remarkably similar situation. In that instance, as another UPS delivery truck obstructs the path forward, the Robotaxi comes to a stop to let its two passengers out just a few feet from their destination.
Once they depart, the Robotaxi successfully reverses and performs a three-point turn to extricate itself from a tight spot. That was all done without human intervention, by correctly identifying the situation.
This second clip is vital because it proves that the Robotaxi's FSD build has the underlying logic and capability to handle these scenarios. It can, and does, use reverse to safely navigate complex situations.
Far from being a failure, this first intervention should be seen as a success for Tesla’s safety methodology. It shows the safety system is working, allowing monitors to mitigate ambiguous events proactively.
More importantly, this incident provides Tesla’s FSD team with an invaluable real-world data point.
By comparing the intervened ride with the successful autonomous one, Tesla’s engineers can fine-tune FSD’s decision-making, which will likely have a positive impact on its edge case handling in the near future.
This is the purpose of a public pilot — to find the final edge cases and build a more robust system, one unpredictable reversing truck at a time.