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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 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 Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.
The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:
“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”
However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.
I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.
The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.
Hurry Mode Results
On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:
Roughly :31 between first touching the center screen and getting the first nag
— TESLARATI (@Teslarati) June 3, 2026
Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.
Here’s an 80-second phone nag test on Tesla FSD v14.3.3.
No alerts, no nagging, no annoyance. https://t.co/1dxvTOw5Cn pic.twitter.com/vYViFpjfoK
— TESLARATI (@Teslarati) May 29, 2026
Mad Max Results
I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.
With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nags on Mad Max https://t.co/qZALU2OujY pic.twitter.com/XddOJ0D47x
— TESLARATI (@Teslarati) June 3, 2026
As well as adjusting Navigation, when I received two nags:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nag while adjusting navigation
Two nags here https://t.co/qZALU2OujY pic.twitter.com/xa3dtaDG1L
— TESLARATI (@Teslarati) June 3, 2026
These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.
These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.
You can watch the full drive on YouTube below:
Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.
The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.
Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:
Unsupervised Robotaxi now in the entire Austin Metro area https://t.co/eXNBdarvVS
— Tesla Robotaxi (@robotaxi) June 3, 2026
This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.
It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.
The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.
Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.
The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.
It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.
It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.
Tesla piggybacks recent Supercharger feature with update that takes it further
Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
