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Details behind Model X owner’s $5M+ class action lawsuit against Tesla
Following our report that a Model X owner has filed a class action law suit against Tesla, claiming a widespread defect in the vehicle’s onboard software causes sudden unattended acceleration (SUA), new details behind the suit have been obtained by Teslarati that shows a legal team aggressively targeting the core component to the Silicon Valley-based electric car maker’s fleet of vehicles.
The class action filed in federal district court claims Ji Chang Son – Korean star residing in Orange County, Calif. – crashed through his garage and into the living room of his home after his Tesla Model X accelerated suddenly and without warning on September 10, 2016, approximately one month after Mr. Son took delivery of the electric SUV. The suit claims that “Tesla has failed to properly disclose, explain, fix, or program safeguards to correct the underlying problem of unintended acceleration”, adding that “over sixteen thousand Model X owners with vehicles that could potentially accelerate out of control.
Son’s attorneys gave the court a full account of the development of the Model X, focusing on the company’s claim that the Model X is “the safest, fastest and most capable sport utility vehicle in history.” On the contrary, according to Son’s attorneys. They allege the Model X has a safety defect that permits the car to accelerate at full speed directly into solid objects, such as the exterior wall of Son’s home. In particular, they point out that 8 written complaints have already been filed with the National Highway Transportation Safety Administration from other Model X owners who report similar occurrences while driving their cars.
The lawsuit reads,
“Irrespective of whether the SUA events in the Model X are caused by mechanical issues with the accelerator pedal, an unknown failure in the electronic motor control system, a failure in other aspects of the electrical, mechanical, or computer systems, or some instances of pedal misapplication, the Model X is defective and unsafe. Tesla’s lack of response to this phenomenon is even more confounding when the vehicle is already equipped with the hardware necessary for the vehicle’s computer to be able to intercede to prevent unintended acceleration into fixed objects such as walls, fences, and buildings.
Despite repeated instances of Model X drivers reporting uncommanded full power acceleration while parking, Tesla has failed to develop and implement computer algorithms that would eliminate the danger of full power acceleration into fixed objects.This failure to provide a programming fix is especially confounding for a vehicle that knows when it is located at the driver’s home and is being parked in the garage, yet carries out an instruction, regardless of whether through an error by the vehicle control systems or by driver pedal misapplication, to accelerate at full power into the garage wall.
Further, not only has Tesla failed to fix the problems, it has chosen instead to follow in the footsteps of other automobile manufacturers and simply blame the driver.”
One problem, according to Son’s attorneys, is the software that controls the Automatic Emergency Braking system. Tesla has programmed that feature to disengage in order to allow drivers to make emergency maneuvers, “in situations where you are taking action to avoid a potential collision. For example:
- You turn the steering wheel sharply.
- You press the accelerator pedal.
- You press and release the brake pedal.
- A vehicle, motorcycle, bicycle, or pedestrian, is no longer detected ahead.”
In other words, say the attorneys, a Model X will drive straight into a solid wall if that is what the system thinks the driver wants it to do. “Apparently, this includes situations where the computer believes, rightly or wrongly, that the driver is commanding full power acceleration directly into fixed objects immediately in front of the vehicle.”
Class action lawsuits are complex and highly specialized legal actions. Federal law requires that the damages alleged for the entire class exceed $5 million. The plaintiff’s attorney have done so by claiming that Tesla is aware of at least two other instances in which drivers allege sudden unintended acceleration occurred while driving their Model X at low speeds. They then extrapolate those numbers to suggest that the rate of SUA incidents attributable to the Model X is 64 per 100,000 vehicles — substantially higher than for any other vehicle in history.
Page 12 of JI CHANG SON vs. TESLA MOTORS class action complaint
They point out that the incidence rate of SUA incidents for Toyota vehicles — which grabbed national headlines in 2010 — was far lower. They then go on to remind the court that Toyota paid several hundred million dollars to SUA victims as well as a $1.2 billion federal fine. Notice that the chart included in the pleadings shows an exaggerated and disproportionate projected SUA incidence rate for the Model X highlighted in bright red.
Tesla says its data retrieved from the vehicle’s blackbox shows the accelerator in Son’s Model X was fully depressed when the accident occurred. The question for the court will be whether the driver pressed the wrong pedal or whether the vehicle accelerated on its own. It is unclear whether a software failure would register the pedal as fully depressed even if it was not physically operated by the driver.
Plaintiffs always have the burden of proving their allegations. Attorneys for injured parties often rely on a legal doctrine known as res ipsa loquitur, which is Latin for “the thing speaks for itself.” Loosely translated, it means “we don’t know what is wrong with your product that you designed and built, but you know or should know.” Res ipsa loquitur shifts the burden of proof onto the defendant, which makes it much easier for a plaintiff to prevail in court.
One advantage the plaintiff gains from filing suit is the ability to discover what information Tesla has that is not yet public. Does Tesla know something it isn’t telling its customers? We may find out as this litigation goes forward.
We’ve provided a copy of the entire class action filing below.
[pdf-embedder url=”http://www.teslarati.com/wp-content/uploads/2017/01/Son-vs-Telsa-class-action-8-16-cv-2282.pdf”]
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.
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.
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.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
