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Rivian patent hints at real-time brake wear monitoring system using driver profiles
Rivian’s attention to detail on its all-electric vehicles is laudable, and a recent patent application by the outdoor adventure company for monitoring brake wear continues that theme. In an application titled “Methods, Systems, and Media for Non-Contact Brake Pad Wear Determination”, a method of estimating the wear on individual breaks via computer algorithms is described. Once calculated, the information is then made available to drivers for planning purposes via the infotainment screen on the R1T pickup truck and R1S SUV. The application published on August 1, 2019 under US Patent Publication No. 2019/0234475.
The background of Rivian’s application stated the following reasons why the invention is needed:
“Current approaches for determining brake pad wear…tend to merely indicate when brake pads are fully worn, for example, using a brake pad indicator that causes the brakes to squeal when the indicator contacts the brake disc or that causes an indication on a dashboard of the vehicle to be presented. It may be useful for a driver to know a current wear condition of the brake pads before the brake pads are fully worn, for example, to plan for vehicle maintenance. However, it can be difficult to determine a current wear of the brake pads.”
While not an official reason listed on the patent, one could also assume brake squealing as an annoying sound in itself would also merit the invention’s usefulness as a reliable preventative.
- Rivian brake-monitoring patent application. | Image: Rivian/USPTO
- Rivian brake-monitoring patent application. | Image: Rivian/USPTO
- Rivian brake-monitoring patent application. | Image: Rivian/USPTO
- Rivian brake-monitoring patent application. | Image: Rivian/USPTO
Overall, Rivian’s application calculates the amount of wear on its vehicles’ brakes by comparing data points gathered from two braking events. The amount of pressure applied plus the distance traveled at two different intervals is collected, then compared to a brake database, and an estimate of the mileage left before a change is needed is provided to the driver. The calculation can also include the driver’s braking history to more accurately reflect the mileage. In other words, if you’re a bit rough on the brake pedal, Rivian’s software will take that into account and probably shorten the mileage you have left before needing replacement parts compared to someone that drives…differently. Here’s the formal language for this ability:
“In some embodiments, the method further comprises associating a braking profile with an operator of the vehicle, wherein the indication of the wear amount of the brake pad includes a number of miles until the brake pad requires replacement that is estimated based on the associated braking profile.”
The method described in the claims of the application that calculate the wear on the brakes indicates a process initiated by the driver, i.e., the driver initiates a brake wear test on the center touchscreen and uses the brakes at two intervals as instructed by the vehicle’s computer to determine the wear percentage. However, the description of the application indicates that the brake testing can also happen in real-time during normal operation. The formal language for this reads as follows:
“…In some embodiments, [the testing] process…can receive a group of brake caliper measurements and corresponding brake pedal travel distances…during application of the brake pedal during normal operation of the vehicle…Additionally, in some such embodiments, [the testing] process can present indications of brake pad wear at any suitable time, such as a next time the vehicle is turned on, and/or at any other suitable time.”
This application is yet the latest nod towards Rivian’s development of a comfortable and luxury driving experience for its vehicle owners. The car maker’s branding as an outdoor electric adventure company really seems to have embraced its mission to get people outside exploring more by making the experience as convenient as possible. Whether it’s ample storage capacity, swapping out cargo modules, extending battery range with a digital jerry can, a portable kitchen built specifically for the R1T pickup truck, or now, being able to easily plan ahead for basic vehicle maintenance by checking a screen, Rivian is continuing its march against barriers to enjoying nature anywhere.
There’s a new phrase that seems to be developing based off of an old one about willpower: “Where there’s a Rivian, there’s a way.”
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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.



