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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.

“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.”

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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.

“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 just made its headlights even better through a software update

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Credit: @jojje167 on X

Tesla just upgraded its headlights through a software update, making them even better without any physical or hardware upgrade.

Tesla’s latest software update is quietly improving nighttime driving for a small number of owners. Version 2026.38 includes a new capability called Dynamic Headlight Leveling.

The feature automatically adjusts the aim of the low beams in response to driving conditions and nearby traffic, with the goal of giving the driver more usable light on the road while reducing glare for oncoming vehicles and traffic ahead.

Unlike Tesla’s matrix high-beam system, which selectively dims individual LED segments to create shadows around other cars, Dynamic Headlight Leveling physically tilts the low-beam projectors. Internal motors respond to changes in vehicle pitch.

When the car accelerates hard, climbs a steep grade, or carries extra weight in the rear, the headlights can otherwise point higher than intended. The software counters that movement in real time so the beam stays aimed at the road surface rather than into the eyes of other drivers.

Early indications reveal the update is reaching a limited set of vehicles, including certain Model 3 and Cybertruck examples in the United States and the United Arab Emirates. The rollout does not appear tied to a single hardware revision, and Tesla has not published a broader schedule. It is simply a common waiting game until your car receives it.

The change arrives against a backdrop of wider complaints about headlight glare. Some earlier Model 3 and Model Y vehicles were the subject of an NHTSA recall related to excessive low-beam glare; the software adjustment offers a potential mitigation for cars equipped with the necessary leveling hardware. It does not replace adaptive high beams where those are already available, nor does it alter the basic low-beam pattern itself.

Instead, it keeps an existing beam pointed where it is most useful.

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For drivers who have received the update, the system requires no new settings or user input. The headlights simply respond as road conditions and traffic change. As the feature reaches more vehicles, it adds another example of Tesla using over-the-air software to refine existing hardware rather than waiting for a new model year. Nighttime visibility and reduced glare for others are the practical results owners are expected to notice first.

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Tesla teases “Halloween Mode” update with Optimus rising from a graveyard

Tesla’s Halloween teaser hides a covered vehicle and an Optimus hand rising from the ground.

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Tesla has started teasing a Halloween software update for its vehicles, with  a short clip on X that reads, “Halloween is coming.” The clip opens on a glowing pumpkin before pulling back to the car’s center touchscreen, where the usual parked visualization has been replaced by a graveyard scene, and the vehicle draped with a white sheet so it reads as a cartoon ghost.

The second detail is a robotic hand clawing its way out of the dirt like a zombie, which looks to be the hand of Tesla’s latest Optimus V3 humanoid robot. While Tesla still has not formally shown Optimus Gen 3 walking around in service, renders pulled from Tesla’s Android app last month gave the clearest look yet, including far more refined hands that Tesla has said carry 22 degrees of freedom. The hand has been the hardest part of the program. Musk has called it the majority of the robot’s engineering difficulty, and Tesla’s patents describe a design driven by tendons with the actuators moved into the forearm.

Tesla Optimus V3 hand and arm details revealed in new patents

Optimus also has a Halloween track record. Last October the robot handed out candy in Times Square, and a costumed “zombie” Optimus shuffled around the Tesla Diner in Los Angeles on Halloween night.

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On the software side, Tesla’s 2025 Holiday Update expanded Santa Mode with a Santa sleigh, snowmen, snow effects, and a festive lock chime, so it wouldn’t be too far fetched if we saw something similar but themed for a  Halloween Mode.

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Tesla says fixes on Full Self-Driving’s two biggest issues are on the way

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Tesla Full Self-Driving is set to receive improvements to address its two biggest issues, according to a company engineer.

Director of Engineering at Tesla AI, Phil Duan, revealed in a post on X that improvements to both pothole avoidance and navigation “are coming,’ something we have heard many times in the past. However, there are a few things that seem to hint that things might be different this time around.

Pothole avoidance, navigation, speed control, and left lane camping are some of the most prevalent and frequently mentioned shortcomings of the Full Self-Driving suite. These are a few of the biggest issues that have kept Tesla Full Self-Driving as a Supervised suite, meaning drivers must remain attentive during operation.

Pothole Avoidance

Pothole avoidance was first mentioned as an “Upcoming Improvement” with the Tesla Full Self-Driving v14.3 update back in early April of this year. It was listed alongside “Expand reasoning to all behaviors beyond destination handling.”

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Tesla is fixing Full Self-Driving’s pothole problem

It’s been six months since we first saw pothole avoidance explicitly mentioned, and it has not moved beyond that and joined the main release notes yet.

Tesla has not shed any light on why pothole avoidance has been such an issue for it to solve, but it also has issues identifying large bumps much of the time, so its modeling of sudden changes in road conditions is likely pretty weak at this particular point. I’ve had more issues with large bumps than potholes, personally, but both are issues that need to be resolved.

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It makes sense that things might be pretty close to being released to the public, as we are going on such an extensive period of time between it being mentioned and it actually being deployed.

Navigation

Navigation is likely the most painful part of using Full Self-Driving, as it routinely takes strange routes, has trouble with local rules (like Except Right Turn Stop Signs in Pennsylvania), and sometimes does not realize that maneuvers it is suggesting are against the law. Turning out of my neighborhood, you cannot turn left, yet my Model Y still suggests it roughly 70 percent of the time when I’m leaving.

However, Tesla might be close to a breakthrough on this. With the Summer Update, Tesla added “Preferred Routes” alongside “Automatic Navigation.”

Preferred Routes prioritized roads that the driver had actually taken before, instead of always defaulting to what the vehicle believes is the most efficient path. This has already solved many of my issues. Formerly, I would turn off the Online Routing setting, and that would eliminate most of my complaints with routing, but then you lose out later on the Live Traffic Visualization.

Tesla’s Navigation has improved tremendously thanks to the Preferred Routes release with the Summer Update, but it still could use some polishing, as it still suggests strange routes from time to time, and it also has a lot of issues getting out of a parking lot. I find that those truly confuse FSD sometimes.

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