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Tesla MIT study concludes that drivers maintain vigilance when using Autopilot
Tesla owners using Autopilot are highly engaged when driving with the feature despite fears to the contrary, according to a study recently published by scientists at MIT titled Human Side of Tesla Autopilot: Exploration of Functional Vigilance in Real-World Human-Machine Collaboration.
The data used in the study was generated from the over 1 billion miles driven by Tesla owners since its activation in 2015, about 35% of which were determined to be assisted by Autopilot. Of these, 18,928 disengagements of Autopilot were annotated, which indicated instances when drivers took over during challenging driving situations. Overall, the numbers demonstrate a high rate of driver vigilance.
Tesla has provided a unique opportunity to form a baseline for objective, representative analysis of real-world use of Autopilot, as stated in the study:
“Due to its scale of deployment and individual utilization, [Tesla’s] Autopilot serves as perhaps the currently best available opportunity to study and understand human interaction with AI assisted vehicles ‘in the wild’…naturalistic driving research can now begin investigating and identify both promising and concerning trends in drivers’ behavioral patterns in the context of Autopilot.”
As automation has expanded over the last several decades, a pattern of overtrust in reliable automated systems has been shown by human behavior research studies. In the context of driving scenarios where property damage, injury, or death are possible consequences, the concern with the transition to semi-autonomous systems relying on driver input to function safely is obviously significant. The results of the MIT study are therefore promising, initially showing an approach to automation in driving systems that’s more careful than other areas.
“The two main results of this work are that (1) drivers elect to use Autopilot for a significant percent of their driven miles and (2) drivers do not appear to over-trust the system to a degree that results in significant functional vigilance degradation in their supervisory role of system operation,” the MIT scientists concluded.
The study further notes that more research will be needed as more data becomes available and more familiarity grows with Autopilot’s features.
Tesla has received a fair amount of criticism and attention whenever an accident involves one of its cars, especially if Autopilot was engaged around the time of the event. However, Tesla consistently maintains its position that the feature is not yet fully autonomous and requires drivers to both pay attention and intervene when necessary while Autopilot is in operation. The program is additionally equipped with several alerts which give drivers audio and visual warnings if hands are not detected on the steering wheel, something found to have been ignored in some prior crash events, playing into concerns the MIT study sought to address.
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Beginning in Q3 2018, Tesla has been releasing quarterly Vehicle Safety Reports providing updated numbers for vehicle incidents occurring both when Autopilot was engaged and when the driver-assist feature was deactivated. For Q3, the company reported one accident or crash-like event for every 3.34 million miles driven with Autopilot active and one event for every 1.92 million miles driven with Autopilot disengaged. In Q4 2018, those numbers dropped slightly, possibly due to winter conditions, to one accident for every 2.91 million miles driven with Autopilot engaged and one accident for every 1.58 million miles driven without.
By comparison, the National Highway Traffic Safety Administration’s (NHTSA) most recent data at the time showed a crash event every 436,000 miles, a figure which includes all vehicles in the US whether or not the cars are equipped with driving enhancement software. Tesla’s numbers further include both accidents that have occurred and “near-misses”, and the NHTSA’s figures only include accidents that actually transpired.
Along with touting a correlation between lower accident rates and Autopilot being engaged, Tesla also maintains its title of producing the safest cars in the world based on NHTSA test results.
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.”
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.
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.
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.
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
