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Tesla says Autopilot was engaged during Model X fatal crash
Tesla recently released an update confirming that Autopilot was activated on the ill-fated Model X when the SUV crashed into a concrete barrier last Friday near Mountain View, CA.
According to the company’s update, the Model X’s Autopilot was engaged with the car’s adaptive cruise control set to minimum in the moments leading up to the crash. Tesla also noted that the Model X’s driver received several visual and one audible hands-on warning earlier on in the drive. The driver’s hands were not detected on the steering wheel for 6 seconds before the accident occurred as well.
Ultimately, Tesla stated that the driver of the ill-fated Model X had about five seconds and 150 meters of unobstructed view of the concrete divider before the accident took place. Logs from the electric SUV, however, revealed that no action from the driver was taken.
Tesla also highlighted that the absence of a crash attenuator — a highway safety device designed to absorb the impact of a collision — was a key reason why the fatal Model X crash was so severe. Tesla noted that it has “never seen this level of damage to a Model X in any other crash.”
As we noted in a previous report, the crash attenuator, better known as a crash cushion, was destroyed in a vehicular accident 11 days before the fatal Model X crash. This is in line with an image that Tesla provided on its first blog post about the incident, when the company showed a picture of the damaged crash cushion a day before the Model X’s collision.
Local news agency ABC7 News was able to get in touch with the driver of the vehicle that collided with the crash cushion 11 days before the Tesla accident. According to the news agency, the previous crash involved James Barboza, who was driving a 2010 Toyota Prius at 70 mph. Barboza walked away from the crash with lacerations on his face and complaints of pain all over his body. The Toyota Prius driver was eventually arrested for driving under the influence.
In a statement to ABC7, Steven Lawrence — a lawyer who specializes in highway safety — stated that the crash cushion, which could have saved the Model X driver’s life, should have been repaired long before the accident. According to Lawrence, 11 days is far too long to fix a crash cushion, especially in areas where the Model X accident took place.
“Some states have as short as a 3-day repair time for high traffic locations. And if you look at the material in California, this thing should have been repaired within a week. Again, there are a lot of questions about what happened and what went wrong, but it should have been repaired in under 11 days.” Lawrence said.
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- The NTSB’s investigation into a fatal Tesla Model X crash continues. [Credit: Dean C. Smith/Twitter]
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- The NTSB’s investigation into a fatal Tesla Model X crash continues. [Credit: Dean C. Smith/Twitter]
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- The NTSB’s investigation into a fatal Tesla Model X crash continues. [Credit: Dean C. Smith/Twitter]
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- The aftermath of a fatal Tesla Model X accident. (Credit: Mercury News/Twitter)
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- The aftermath of a fatal Tesla Model X accident. [Credit: Dean C. Smith/Twitter]
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- The aftermath of a fatal Tesla Model X accident. (Credit: ABC News Radio/Twitter)
CalTrans issued a statement to the local news agency on Thursday, addressing the delay in its repair of the road safety device. While CalTrans admitted that the crash cushion should have been repaired within 7 days after the 2010 Prius collided with the crash attenuator, the agency noted that storms in the area delayed the repair.
“Once our Maintenance team has been notified, the Department’s goal is to repair or replace damaged guardrail or crash attenuators within 7 days or 5 business days, depending on weather. These are guidelines that our Maintenance staff follow.
“However, as in this case, storms can delay the fix. In this incident, as soon as maintenance was aware of the damaged attenuator, efforts were made to place cones or safety barricades at the site, and the replacement work was scheduled.”
As noted in a previous report, the Tesla Model X has a 5-star safety rating from the National Highway Traffic Safety Administration (NHTSA), due to its safety features such as its 12-airbag system and its huge crumple zone. Roughly 85,000 successful Autopilot trips have been done by Tesla owners in the same stretch of road as the ill-fated Model X since the driver-assist feature was introduced in 2015, with around 200 trips being conducted every day.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
