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Tesla turns up vehicle safety with clever ‘crash can’ patent
Tesla’s electric cars are already among the safest vehicles on the road today with their impressive safety ratings. But even the best cars still have room for improvement, and one can count on Tesla to be the manufacturer that will do what it can to make its already-safe vehicles even safer. An example of this could be found in a recently published patent that describes a “crash can” that can help protect occupants better in the event of a collision.
The patent, titled “ADVANCED THIN-WALLED STRUCTURE FOR ENHANCED CRASH PERFORMANCE” describes a specific design for a “crash can,” a thin-walled metal structure that is built into the crash zones of a vehicle. These metal structures are built to absorb the energy of an impact, and are designed to deform in a stable manner during events such as a crash. Crash cans are typically a square, single-cell tube directly mounted to the front of the frame of the vehicle.
Tesla’s crash can patent takes the same concept but raises it up a couple of notches higher. Instead of using a simple square, single-cell tube, Tesla’s patent describes a “multi-cell structure that includes at least four hollow cuboids.” The four walls of the hollow cuboids meet at 90-degree angles and at least two of the cuboids share a wall. Tesla describes its design in the section below.
“In some embodiments a crash can for a vehicle includes a multi-cell structure that includes a hollow cuboid and four hollow isosceles trapezoidal prisms. The hollow cuboid has four walls and the four hollow isosceles trapezoidal prisms each have a long base, a short base, and two legs. The four hollow isosceles trapezoidal prisms are arranged around the hollow cuboid such that the long base of each hollow isosceles trapezoidal prism shares one of the walls of the hollow cuboid.”
- (Credit: US Patent Office)
- (Credit: US Patent Office)
Illustrations of Tesla’s “crash can” patent. (Credit: US Patent Office)
This updated design, while seemingly a minor change, actually improves the safety of a vehicle during a crash. According to Tesla, the crash can design in its recently-published patent provides a more stable deformation process. This increases the amount of energy that can be absorbed in a collision.
“One advantage of the various embodiments of the crash cans disclosed herein is that the multi-cell structure of the crash cans provides a more stable form of plastic deformation when the crash can is subject to the force of a collision relative to a single cell (tube) structure. Further, the various geometries described herein may further provide more stable plastic deformation relative to conventional geometries. As described herein, plastic deformation is the process of absorbing energy when the crash can is subject to a collision. Various exemplary crash cans provided herein increases plastic deformation, and thus the amount of energy absorbed, by increasing the probability that the crash cans buckle in a progressive manner. Thus, the multi-cell structure of the exemplary crash cans increases the probability that when subjected to axial force the crash cans will buckle in a stable top-down, progressive folding of the structure.
“Increasing plastic deformation in this manner grants the multi-cell crash can several advantages. For example, increasing plastic deformation in turn increases the amount of energy that will be absorbed during a collision, resulting in lower deceleration for the occupant(s) and critical components of a vehicle involved in a collision. This, in turn, results in an overall safer experience for the occupant(s) and critical components, providing for a lower chance of injury or damage. Additionally, increasing the probability that the multi-cell crash can buckles in a stable manner increases the predictability of how the crash can will react when subject to a collision, which in turn increases the predictability of how the rest of the vehicle will react. This allows for greater predictability of what an occupant will experience and allows for more precise planning on how to keep the occupant safe.”
The full text of Tesla’s novel “crash can” patent could be accessed here.
Among the carmakers in the auto segment today, Tesla is arguably the most obsessive when it comes to its vehicles’ safety. Each one of Tesla’s electric cars has performed well in crash tests, with the Model X SUV proving to be near-impossible to topple, and the Model 3 acing the safety tests of the NHTSA, Euro NCAP, ANCAP, and even the IIHS. With improvements such as those described in its recently-published “crash can” patent, Tesla’s electric cars today, as well as its upcoming vehicles, could prove even safer.
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Tesla crosses major Unsupervised Self-Driving milestone
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
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Tesla Robotaxi will be a 24/7 service: here’s when
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
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Tesla Full Self-Driving will now overtake manual driving to avoid disaster
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.

