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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 Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.
The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.
This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.
Following future rollout of FSD V14 Lite for HW3 vehicles in the US, we plan on expanding V14 Lite to additional international markets.
This update ensures that HW3 vehicle owners will continue to benefit from ongoing software updates.
Since international rollout is subject to…
— Tesla (@Tesla) April 29, 2026
It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”
Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”
Anyone who purchased full self-driving will get FSD computer upgrade for free. This is the only change between Autopilot HW2.5 & HW3. Going forward “HW3” will just be called FSD Computer, which is accurate. No change to vehicle sensors or wire harness needed. This is v important. https://t.co/lICMpT7xnX
— Elon Musk (@elonmusk) March 29, 2019
However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”
Tesla has made some effort to remedy these Hardware 3 owners by offering:
- Discounted trade-ins toward AI4 cars
- Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
- Full Self-Driving v14 Lite
The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.
Expectations for Tesla v14 Lite for Hardware 3 Owners
The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.
Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.
Tesla reveals its plans for Hardware 3 owners who are eager for updates
This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.
There should also be a handful of additional features that are available on AI4 cars, such as:
- Starting Full Self-Driving from Park
- Auto Shift
- Streaks
- Speed Profiles
- Improved Dynamics, like Pulling Over for Emergency Vehicles
Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.
We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.
Elon Musk
SpaceXAI just launched into your kitchen with their new app
SpaceXAI just powered its first consumer app and it predicts what you want to buy.
SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.
Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.
Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.
Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.
Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”
Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO
The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.
Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.
This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.
The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.
Tesla supplements Holiday Update by sneaking in new Full Self-Driving version
Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.
Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:
Supercharger update now shows type of Tesla at charger as well.
Pretty cool. pic.twitter.com/J3NRSIgM0m
— DennisCW | wen my L (@DennisCW_) June 2, 2026
This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.
Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.
Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.
Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.
In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.
As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.
With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.
Tesla Hardware 3 owners could be made whole this month
SpaceXAI just launched into your kitchen with their new app
