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Watch Tesla’s FSD tackle water cup challenge, dirt roads in China

How does Tesla’s Full Self-Driving face off against competitors in China when it comes to smoothness and scalability?

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Credit: 王船船 | Douyin (via Tesla on X)

Tesla’s Full Self-Driving (FSD) started going out for testing in China last month, representing the first market outside of North America to get the software. Amidst competition in the automated driving space from a number of other Chinese companies, Tesla’s FSD seems to be impressing in early reviews, with recent reviews highlighting both the software’s smoothness and its ability to adapt and perform well on non-traditional roads.

In a Saturday video originally posted by user 王船船 on Douyin, the Chinese version of TikTok, a driver utilizes the Supervised FSD system while performing what’s called the “water challenge,” in which a cup of water is balanced on the driver’s side window ledge to see if driving is smooth enough to avoid spilling.

The drive spans a little more than four minutes, and the system manages to make it through without the water spilling in any substantial quantities. The driver mostly remains on city streets, but you can see a handful of quick, unexpected stops, turns, and other maneuvers that one might expect to make the cup tip completely.

The video was also reposted on X by Tesla’s main account, with the company highlighting the system’s “maximum smoothness” as demonstrated in the video. Tesla VP of AI Ashok Elluswamy also reposted the video, saying in a separate follow-up post that “FSD’s been prepared for this one.”

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Although Tesla’s FSD system didn’t have access to real-world driving data from the company’s vehicles at the time of its launch in China, Elon Musk recently explained that the company used publicly available video from the internet to help pre-train FSD for Chinese streets and traffic laws.

In addition to helping with city streets, Tesla has explained in the past that its camera- and video-based FSD neural network training makes the system easily scalable to multiple countries, fringe traffic cases, and even less traditional roads.

As another example of this in China, FSD testers also took to some dirt roads last week, showing just how well the software seems to handle some seemingly-deep and super-narrow back roads. You can see excerpts from this video below, or check out the full 25-minute version from user AE68 on Douyin.

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READ MORE ON TESLA CHINA: Cheaper Tesla Model Y may launch in China

Tesla’s FSD in China amidst local competition

Tesla officially launched a localized data privacy version of FSD Supervised in China last month, The launch came amidst a headstart from multiple competitors in the autonomous driving space, including from Chinese automakers Baidu, Huawei, and still others.

The Avatr 11 electric vehicle (EV), a jointly created project from Changan New Energy, CATL, and Huawei, was recently seen being tested by Out of Spec’s Kyle Conner. The system uses Huawei’s latest automated driving system technology, Qiankun ADS 3.2, which Conner recently said was “the best driver assistance he’s ever experienced” in a recent review on his trip to China.

You can see this video and an additional video from Conner and Out of Spec discussing the emerging autonomous vehicle industry in China below. It’s also worth noting that both of these were released just a few weeks before Tesla’s first version of FSD launched in the country.

The Best FSD System In China! 1 Hour Drive Using Huawei Qiankun ADS 3.2 Installed In Avatr 11 (2/1/25)

The EV Industry Isn’t Ready For China’s FSD Breakthrough (2/2/25)

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Elon Musk clarifies the holdup with Tesla Full Self-Driving launch in Europe

 

Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Tesla Robotaxi will be a 24/7 service: here’s when

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Credit: @AdanGuajardo/X

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.

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.

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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

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Credit: Tesla

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.

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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.

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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.

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Tesla Cybercab launch catches NHTSA’s attention who wants to know more

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(Credit: Teslarati)

Tesla launched the all-electric, steering wheel-less, and pedal-less Cybercab last night at a quiet and small event in downtown Austin, Texas.

The launch, which marked the beginning of unsupervised ride-hailing for Tesla’s Robotaxi platform with Cybercab, has already caught the attention of the National Highway Traffic Safety Administration (NHTSA) who has more questions.

NHTSA opened an Audit Query (AQ) into the Cybercab’s Federal Motor Vehicle Safety Standards (FMVSS) certification that Tesla gave the vehicle. Manufacturers self-certify vehicles much of the time to avoid excessive regulatory delays.

Tesla Cybercab interior, note the lack of steering wheel and pedals. (Credit: @niccruzpatane/X< /a>)

However, the agency needs more information; it said in a summary:

“On September 3, 2026, Tesla began commercial deployment with a small number of its Cybercab vehicles in Austin, Texas. Tesla notified the Agency that it certified those Cybercab vehicles as compliant with all applicable Federal Motor Vehicle Safety Standards (FMVSS). Tesla also notified the Agency that it plans to gradually expand commercial deployment of the Cybercab to include additional vehicles and locations.”

It also went on to state that the Cybercab lacks traditional automotive controls, which is a groundbreaking move. The process is entirely new to the NHTSA, which gives the agency some leverage to put Tesla’s launch under a microscope:

“The vehicles lack permanently attached, conventional manual controls, such as a brake pedal, gas pedal, steering wheel, and mirrors. NHTSA is opening this AQ to examine the process and technical data on which Tesla relied when certifying the Cybercab and related issues. Among other things, NHTSA will consider the extent to which Tesla’s certification depended on determinations that certain FMVSS are inapplicable to the Cybercab.”

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Tesla has added 45 Cybercab units to its fleet of Robotaxi-enabled cars in Austin, according to public documents the company submitted to the State of Texas over the past week. Enabling this level of self-driving is something Tesla has worked toward for many years, and now that it is finally here, it seems more than reasonable that regulatory agencies will have some questions.

Many outlets might try to frame this as a negative, but it is truly an agency looking to gain more information about groundbreaking tech that Tesla has been developing for years.

In an effort to keep riders, pedestrians, and property safe, any and all data accumulated from these first days, weeks, and months of rides will likely be shared with the NHTSA to enable broader rollout strategies across the United States and more in the future.

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