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Tesla Model S on Autopilot crashes into stalled van on highway
A Tesla Model S crashes into the back of a stalled vehicle on a highway. Who is responsible, Autopilot, TACC, or the driver? Ultimately, we know the answer but not everyone wants to admit it.
A Tesla Model S on Autopilot crashed into the back of a stalled van in the high speed lane of a highway this week. The owner Chris Thomann who caught the accident through his dash cam believes it shows the Traffic Aware Cruise Control/Autopilot feature of his car malfunctioned. According to the description on Thomann’s YouTube video, he claims Autopilot and TACC have worked flawlessly many times before, but this time “The forward collision warning turned on way too late, it was set to normal warning distance”.
Updated: The original YouTube video has been marked as private so we added this animated gif via CNET showing the events of what happened.
There have been several instances lately in which Tesla drivers claim their cars malfunctioned, leading to collisions. Is there something wrong with these systems that people should be aware of?
The answer appears to be “No.” On Reddit, Tesla owner Ricodic took the time to post this language from page 69 of the Model S owner’s manual:
Warning: Traffic-Aware Cruise Control can not detect all objects and may not brake/decelerate for stationary vehicles, especially in situations when you are driving over 50 mph (80 km/h) and a vehicle you are following moves out of your driving path and a stationary vehicle or object, bicycle, or pedestrian is in front of you instead. Always pay attention to the road ahead and stay prepared to take immediate corrective action. Depending on Traffic-Aware Cruise Control to avoid a collision can result in serious injury or death. In addition, Traffic-Aware Cruise Control may react to vehicles or objects that either do not exist or are not in the lane of travel, causing Model S to slow down unnecessarily or inappropriately.
The problem is not with the software, it is with human drivers. It’s not that we don’t trust the technology; it’s that we trust it too much. We assume it means we can read the paper on the way to work or fall asleep at the wheel. We get lulled into a sense of false security by how well Autopilot and TACC work most of the time. The failure is in the human brain, which needs a moment or two to recognize that an emergency is in the making and that it is time to re-assert control over the vehicle.
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Tesla owner Jarrod Overson spoke about this candidly in a post on Medium after his car suffered a collision in April. “Once I recognized the car was stopped in front of me, I explicitly remember panicking with the following thoughts going through my head: “Does my car see this? Is it going to do anything? NO. NO IT ISN’T. EMERGENCY.” In retrospect, the actions I needed to take were obvious . I should have regained control immediately. That half of a second or more probably would have made a lot of difference. The problem is that my brain wasn’t primed to have that conversation with itself. Now it is.”
Overson knew some would take him to task for his error in judgment. “I’m not looking forward to the comments calling me stupid for not doing this automatically, but I felt like it’s an important topic to be open about. I’d wager we all had a time in our lives where we didn’t know the extent of some technology, trusted it too far, and had to recalibrate after we understood the limits. Now we might just have to be a little bit luckier to get to that recalibration stage.”
It’s what autonomous driving experts refer to as “the handoff,” that brief period of time between when everything is going along serenely and when it is not. It’s when the computer suddenly finds itself in one of what Elon Musk calls a “corner case.” Those are instances that requires human input. Often, drivers have less than a second to react.
As good as Autopilot is — and it is getting better all the time — Tesla drivers still must be aware that the company and the software expect them to step in when necessary. Many put too much faith in the technology and are willing to abdicate ultimate responsibility for the operation of the car to machines.
The glowing praises we often hear from Elon make it easy to do. Perhaps Musk and Tesla could back their statements about the wonders they have created down a notch. Not everyone reads every page of the owner’s manual and even fewer commit everything found in the instructions to memory.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Tesla headlights have caused a recall of over 20,000 of the company’s two most popular vehicles, the Model 3 and Model Y, due to the low-beam bulb exceeding the maximum allowed intensity according to federal standards.
Tesla initiated the recall with the National Highway Traffic Safety Administration (NHTSA) this morning, stating that the low-beam output “exceeds the maximum allowed intensity in the outer upper-right and outer upper-left areas of the 10U and 90U zone, as prescribed in FMVSS No. 108.”
Tesla sourced the impacted headlights from Marelli Automotive Lighting, a Mexico-based company. The recall impacts 2020-2023 Model Y vehicles and 2017-2023 Model 3 vehicles. It is estimated that every VIN in this recall is impacted by the defect.
🚨 Tesla is recalling 20,349 2020-23 Model Y vehicles and 2017-23 Model 3 vehicles due to an excessively bright headlamp low beam.
Currently, there is no remedy plan in place, as it is still being developed. pic.twitter.com/y34cIO2U0B
— TESLARATI (@Teslarati) August 11, 2026
Typically, Tesla would remedy recalls of this nature through an Over-the-Air software update, which has been a major focus of criticism by the company and its supporters because the NHTSA still refers to it as a “recall,” even though it requires no action by the vehicle owner. The fix is shipped over the internet and downloaded to the car.
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However, there appears to be a potentially different solution for this problem. Tesla has not developed a remedy for this issue, so it could potentially be on the way. The big issue appears to be the fact that these recalled lamps are out of production, and this is an old body style for both vehicles. The headlights and front-end designs are completely different.
Tesla switched to another supplier when the affected headlight design was discontinued. It plans to begin notifying owners of their remedy options by September 15.
Tesla filed a petition protesting the recall to fix the vehicles’ headlight issue, but the NHTSA denied it. Now, Tesla will come up with a solution to fix it.
Tesla has one big financial question to answer for investors: Morgan Stanley
SpaceX AI investment gamble will make it a big winner, firm says
