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Tesla designs safer airbag deployment system through seat sensors in new patent

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Tesla’s electric cars are among the safest on the road, so much so that the Model 3, Model S, and Model X are among the NHTSA’s top vehicles with the lowest probability of injury in the event of an accident. Thanks to Tesla’s use of ultra-high-strength steel and aluminum, as well as the vehicles’ extra large crumple zones due to their all-electric design, the company’s electric cars are capable of protecting their occupants when untoward events happen on the road.

If a recently published patent application is any indication, though, it appears that Tesla is exploring more ways to make its vehicles even safer. Tesla’s recent patent, titled “Sensors for Vehicle Occupant Classification Systems and Methods,” taps into the company’s prowess in tech by using a system that alows cars to detect and/or classify their occupants based on readings from a series of sensors in the seats. With such a system in place, safety features could activate in a way that is optimized for passengers.

Diagrams depicting Tesla’s “Sensors for Vehicle Occupant Classification Systems and Methods” patent. (Credit: US Patent Office)

Tesla notes that cars on the road today are becoming safer overall, thanks to systems that monitor operations while the vehicle is in motion and features that provide coordinated alerts and assistance as needed. While such processes make vehicles safe, though, Tesla states that there is still a large area for improvement. One such area, according to the electric car maker, is in the way airbags deploy in the event of an accident.

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“Difficulties remain in reliably detecting the presence of vehicle occupants and accurately classifying them as children, relatively small adults, and/or according to other classifications, and particularly in differentiating between classifications. Accurate classification can be critical when the vehicle is attempting to assist or enact safety measures to protect the occupant.

“In particular, airbag deployment can be adjusted to reduce risk of injury caused by the airbag while maintaining safety of the occupant during a collision. However, while reduced-force airbag deployment is recommended for relatively small adult females, it is not recommended for young children, even though the young children can reach heights and weights approaching those of the relatively small adult females. Thus, there is a need for an improved methodology to provide reliable and accurate vehicle occupant classification, particularly in the context of controlling an occupant restraint system that can apply force to an operator of the vehicle.”

Tesla’s patent application explores the use of sensors placed on the vehicle’s seats that enable the cars to classify their occupants. By classifying the size, weight, and body type (among others) of a passenger, the car would be able to deploy airbags in the safest way possible during an accident. Tesla describes this system as follows.

“In accordance with various embodiments of the present disclosure, occupant detection and classification may be provided by an occupant weight sensor, an occupant presence sensor, and a logic device configured to convert sensor signals provided by the occupant weight sensor and the occupant presence sensor into an estimated occupant weight and an occupant presence response, which may be used together to reliably detect and classify the occupant with increased sensitivity, accuracy, and granularity compared to conventional detection systems.

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“In particular, embodiments of the present occupant classification system may be employed to detect and differentiate a child from a relatively small woman or man and disable, partially enable, or fully enable an airbag as appropriate. Such occupant classification systems may be implemented with various types of user feedback mechanisms, including reporting detections and classifications both locally and remotely, such as to a smartphone, for example, and reporting potentially unsafe conditions and/or undesired operation of the vehicle, as described herein.”

With this system in place, Tesla’s electric cars would be even safer than they already are. If any, this would widen the gap further between Tesla’s vehicles and conventional cars, many of which are bogged down in frontal collisions due to the presence of a large, heavy engine under the hood. That said, this recent patent application all but emphasizes Tesla’s proactive nature and the company’s tendency to always make efforts to improve.

This particular nature was emphasized by Elon Musk on Twitter last October, when he explained that there is “no such thing” as a “full refresh” or even a model year at Tesla. In his tweet, Musk stated that all the company’s vehicles are partially upgraded every month “as soon as a subsystem is ready for production,” thereby ensuring buyers that they are getting the best vehicles available at their time of purchase. This, coupled with Tesla’s trademark over-the-air updates — which give new features from driver assist functions such as Navigate on Autopilot, to fun, quirky things like the Romance Mode Easter Egg — truly make the company’s electric cars unique on the road.

The full text of Tesla’s recent patent application could be accessed here.

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla owners surpass 8 billion miles driven on FSD Supervised

Tesla shared the milestone as adoption of the system accelerates across several markets.

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Credit: Tesla

Tesla owners have now driven more than 8 billion miles using Full Self-Driving Supervised, as per a new update from the electric vehicle maker’s official X account. 

Tesla shared the milestone as adoption of the system accelerates across several markets.

“Tesla owners have now driven >8 billion miles on FSD Supervised,” the company wrote in its post on X. Tesla also included a graphic showing FSD Supervised’s miles driven before a collision, which far exceeds that of the United States average. 

The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable. As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.

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At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.

Tesla also recently updated the safety data for FSD Supervised on its website, covering North America across all road types over the latest 12-month period.

As per Tesla’s figures, vehicles operating with FSD Supervised engaged recorded one major collision every 5,300,676 miles. In comparison, Teslas driven manually with Active Safety systems recorded one major collision every 2,175,763 miles, while Teslas driven manually without Active Safety recorded one major collision every 855,132 miles. The U.S. average during the same period was one major collision every 660,164 miles.

During the measured period, Tesla reported 830 total major collisions with FSD (Supervised) engaged, compared to 16,131 collisions for Teslas driven manually with Active Safety and 250 collisions for Teslas driven manually without Active Safety. Total miles logged exceeded 4.39 billion miles for FSD (Supervised) during the same timeframe.

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The Boring Company’s Music City Loop gains unanimous approval

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project.

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(Credit: The Boring Company)

The Metro Nashville Airport Authority (MNAA) has approved a 40-year agreement with Elon Musk’s The Boring Company to build the Music City Loop, a tunnel system linking Nashville International Airport to downtown. 

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project. Under the terms, The Boring Company will pay the airport authority an annual $300,000 licensing fee for the use of roughly 933,000 square feet of airport property, with a 3% annual increase.

Over 40 years, that totals to approximately $34 million, with two optional five-year extensions that could extend the term to 50 years, as per a report from The Tennesean.

The Boring Company celebrated the Music City Loop’s approval in a post on its official X account. “The Metropolitan Nashville Airport Authority has unanimously (7-0) approved a Music City Loop connection/station. Thanks so much to @Fly_Nashville for the great partnership,” the tunneling startup wrote in its post. 

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Once operational, the Music City Loop is expected to generate a $5 fee per airport pickup and drop-off, similar to rideshare charges. Airport officials estimate more than $300 million in operational revenue over the agreement’s duration, though this projection is deemed conservative.

“This is a significant benefit to the airport authority because we’re receiving a new way for our passengers to arrive downtown at zero capital investment from us. We don’t have to fund the operations and maintenance of that. TBC, The Boring Co., will do that for us,” MNAA President and CEO Doug Kreulen said. 

The project has drawn both backing and criticism. Business leaders cited economic benefits and improved mobility between downtown and the airport. “Hospitality isn’t just an amenity. It’s an economic engine,” Strategic Hospitality’s Max Goldberg said.

Opponents, including state lawmakers, raised questions about environmental impacts, worker safety, and long-term risks. Sen. Heidi Campbell said, “Safety depends on rules applied evenly without exception… You’re not just evaluating a tunnel. You’re evaluating a risk, structural risk, legal risk, reputational risk and financial risk.”

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Tesla announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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