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Stanford studies human impact when self-driving car returns control to driver
Researchers involved with the Stanford University Dynamic Design Lab have completed a study that examines how human drivers respond when an autonomous driving system returns control of a car to them. The Lab’s mission, according to its website, is to “study the design and control of motion, especially as it relates to cars and vehicle safety. Our research blends analytical approaches to vehicle dynamics and control together with experiments in a variety of test vehicles and a healthy appreciation for the talents and demands of human drivers.” The results of the study were published on December 6 in the first edition of the journal Science Robotics.
Holly Russell, lead author of study and former graduate student at the Dynamic Design Lab says, “Many people have been doing research on paying attention and situation awareness. That’s very important. But, in addition, there is this physical change and we need to acknowledge that people’s performance might not be at its peak if they haven’t actively been participating in the driving.”
The report emphasizes that the DDL’s autonomous driving program is its own proprietary system and is not intended to mimic any particular autonomous driving system currently available from any automobile manufacturer, such as Tesla’s Autopilot.
The study found that the period of time known as “the handoff” — when the computer returns control of a car to a human driver — can be an especially risky period, especially if the speed of the vehicle has changed since the last time the person had direct control of the car. The amount of steering input required to accurately control a vehicle varies according to speed. Greater input is needed at slower speeds while less movement of the wheel is required at higher speeds.
People learn over time how to steer accurately at all speeds based on experience. But when some time elapses during which the driver is not directly involved in steering the car, the researchers found that drivers require a brief period of adjustment before they can accurately steer the car again. The greater the speed change while the computer is in control, the more erratic the human drivers were in their steering inputs upon resuming control.
“Even knowing about the change, being able to make a plan and do some explicit motor planning for how to compensate, you still saw a very different steering behavior and compromised performance,” said Lene Harbott, co-author of the research and a research associate in the Revs Program at Stanford.
Handoff From Computer to Human
The testing was done on a closed course. The participants drove for 15 seconds on a course that included a straightaway and a lane change. Then they took their hands off the wheel and the car took over, bringing them back to the start. After familiarizing themselves with the course four times, the researchers altered the steering ratio of the cars at the beginning of the next lap. The changes were designed to mimic the different steering inputs required at different speeds. The drivers then went around the course 10 more times.
Even though they were notified of the changes to the steering ratio, the drivers’ steering maneuvers differed significantly from their paths previous to the modifications during those ten laps. At the end, the steering ratios were returned to the original settings and the drivers drove 6 more laps around the course. Again the researchers found the drivers needed a period of adjustment to accurately steer the cars.
The DDL experiment is very similar to a classic neuroscience experiment that assesses motor adaptation. In one version, participants use a hand control to move a cursor on a screen to specific points. The way the cursor moves in response to their control is adjusted during the experiment and they, in turn, change their movements to make the cursor go where they want it to go.
Just as in the driving test, people who take part in the experiment have to adjust to changes in how the controller moves the cursor. They also must adjust a second time if the original response relationship is restored. People can performed this experiment themselves by adjusting the speed of the cursor on their personal computers.
“Even though there are really substantial differences between these classic experiments and the car trials, you can see this basic phenomena of adaptation and then after-effect of adaptation,” says IIana Nisky, another co-author of the study and a senior lecturer at Ben-Gurion University in Israel “What we learn in the laboratory studies of adaptation in neuroscience actually extends to real life.”
In neuroscience this is explained as a difference between explicit and implicit learning, Nisky explains. Even when a person is aware of a change, their implicit motor control is unaware of what that change means and can only figure out how to react through experience.
Federal and state regulators are currently working on guidelines that will apply to Level 5 autonomous cars. What the Stanford research shows is that until full autonomy becomes a reality, the “hand off” moment will represent a period of special risk, not because of any failing on the part of computers but rather because of limitations inherent in the brains of human drivers.
The best way to protect ourselves from that period of risk is to eliminate the “hand off” period entirely by ceding total control of driving to computers as soon as possible.
Tesla CEO Elon Musk posted a photo of himself standing with the Optimus production team inside Tesla’s Fremont factory, arms crossed amid workers in hard hats and safety vests. The image captures a pivotal industrial shift: the same facility space once dedicated to building Tesla’s flagship Model S sedan and Model X SUV is now home to the company’s humanoid robot manufacturing line.
Walking the Optimus production line in Fremont pic.twitter.com/ABS0tuRibW
— Elon Musk (@elonmusk) July 1, 2026
Tesla’s Fremont Factory, acquired in 2010 from the former NUMMI joint venture between Toyota and GM, has been the company’s original U.S. manufacturing hub since Model S production began in 2012.
The Model X followed soon thereafter. These premium vehicles offered lower annual volumes, recently around 30,000 combined, compared to the high-volume Model 3 and Model Y lines that continue around the site. Over their combined run, the S and X accounted for roughly 610,000 units.
In late January 2026, during Tesla’s Q4 2025 earnings call, Elon Musk announced the end of Model S and Model X production in Q2 2026. The final vehicles rolled off the line in early May. Rather than retooling for another vehicle, Tesla chose to convert the dedicated S/X assembly area into a dedicated Optimus Gen 3 production line.
Model 3 and Y manufacturing remains unaffected. Tesla’s official Fremont Factory page now lists Optimus alongside the 3 and Y as core products.
The conversion was executed with remarkable speed. After production stopped, crews dismantled the existing vehicle line and installed entirely new modular equipment—including lines sourced from Germany and dozens of sub-lines for actuators, batteries, and other components—in roughly four months.
Musk described the timeline as “insanely fast,” noting it would be unprecedented for any other manufacturer. Initial Optimus output is expected to ramp slowly due to the robot’s roughly 10,000 unique parts and the brand-new production processes involved. The Fremont line targets an eventual capacity of 1 million Optimus units per year.
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Optimus Development Timeline
- August 19, 2021: Optimus (then called Tesla Bot) formally announced at Tesla’s first AI Day. A concept video showed a person in a suit demonstrating the vision for a general-purpose humanoid capable of dangerous, repetitive, or boring tasks using the same AI architecture as Full Self-Driving.
- 2022: Early prototypes displayed. At the second AI Day in September, semi-functional units demonstrated walking across a stage and basic arm movements
- 2023: September videos showed improved capabilities, including sorting colored blocks, precise limb awareness, and holding a Yoda pose.
- 2024-early 2025: Factory integration videos showed Optimus navigating workspaces and handling objects like battery cells.
- January 2026: Gen 3 mass-production activities began at Fremont, with reports of over 1,000 Gen 3 units already operating inside the factory for real-world learning and AI training
- April 2026: Musk confirms Optimus production on converted Fremont line would begin in late July or August 2026. The Gen 3 reveal, originally eyed for Q1, was pushed closer to production start. A second, much larger Optimus factory at Giga Texas is under construction, with volume production targeted for Summer 2027 and long-term capacity of 10 million units annually
- July 1, 2026: Musk’s on-site visit and team photo confirm the Optimus line is operational and the transition is actively progressing
Tesla positions Optimus as potentially its largest project ever, leveraging vertical integration, AI expertise, and car-like manufacturing know-how to scale humanoid robots first for its own factories and later for broader industrial and consumer use.
The Fremont conversion serves as a critical proving ground for this ambitious new chapter in Tesla’s already-rich history.
Investor's Corner
Tesla gets its latest short from Michael Burry: ‘Happy it jumped back to this level’
Tesla short seller Michael Burry, the subject of the film “The Big Short,” where he was portrayed by Steve Carell, has revealed he has opened a new bet against the stock.
In a new update to his Substack newsletter in a post titled “Trading Post June 30, 2026,” Burry revealed a new set of bets against Tesla, Caterpillar, NVIDIA, Applied Materials Inc., and the iShares Semiconductor ETF.
In regard to Tesla, Burry wrote:
“And finally I shorted Tesla at 416.22. Happy it jumped back to this level.”
This means Burry likely opened his new short position after the company’s recent rally on Wall Street, which saw Tesla shares sink in mid-May, only to recover to well over the $400 mark. Currently, shares trade at around $427.
The company saw a big Tuesday as shares climbed considerably, over 10 percent. The size of the Tesla short was not provided, nor did Burry give any information on the position’s structure, the number of shares, dollar value, or whether options were used in the short.
The Tesla and SpaceX merger everyone is talking about is quietly building
Over the years, Burry has been one of the more vocal critics of Tesla, calling its share price “media inflated,” and saying it was “ridiculously overvalued” as recently as December.
The company has largely transitioned away from being known as an automotive company and instead is much more widely regarded as an AI play, mostly due to its Full Self-Driving efforts, Optimus robot development, and data collection related to both.
This has not pulled those skeptics away from being vocal about their distaste for how Tesla is valued, but there’s no denying that the company is a global force in many things, including sustainable energy, automotive, and AI.
Wedbush Securities is initiating stock coverage on SpaceX (NASDAQ: SPCX), marking the first comments on the company since it went public several weeks ago. Wedbush and its analyst handling coverage, Dan Ives, are widely bullish on fellow Musk company Tesla (NASDAQ: TSLA).
Ives wrote his first note initiating coverage of SpaceX shares on Wednesday with a $190 price target and an ‘Outperform’ rating. The firm believes the company is well positioned off of its IPO because of its wide array of projects, including AI compute power and infrastructure, connectivity projects, and launches.
“We view SpaceX as one of the most differentiated assets within the tech market with a strong footprint across its three core markets, with Starlink driving success with connectivity,” Ives wrote, “Starship launches leading to a demand flywheel and increasing deal flow for its Colossus clusters.”
Elon Musk called it Epic: The full story of SpaceX’s Starship Flight 12
Wedbush leans heavily on Starlink, which they say is the “profitability driver given the strength of its recurring revenue base of ~12 million subscribers as of June 5th.” Ives believes Starlink is still in the “early innings” of penetrating the global telecommunications and broadband market, as it only holds less than a 1 percent share. However, this number is sure to increase over time.
It also highlights the importance of Starship, which it says is an “essential layer” of SpaceX’s overall success. SpaceX developing and displaying the ability to reuse rockets is a major cost and reliability advantage “as it reduces the necessary hardware launch costs while generating a feedback loop for future flights to improve their launch flight rate without accelerating capex spend.”
Finally, SpaceX’s recent AI/Compute projects are also very elementary, Ives writes. It is worth mentioning Wedbush said its $190 price target is derived from a valuation forecast that sees the company yielding roughly $2.48 trillion of implied enterprise value.
There are also some factors that Wedbush did not take into account with its initial coverage. The firm wrote in the note:
“We note that there is optional value coming from Starship’s accelerating scale towards sub-$200/kg unit economics, orbital data centers, and enterprise AI monetization as these factors could drive meaningful upside but these face major hurdles, so we do not take that into account with our valuation.”
SpaceX shares are down just over 2 percent today, trading at around $167 at the time of publication.
Tesla Optimus project fires up as Musk sees production line progress
Tesla gets its latest short from Michael Burry: ‘Happy it jumped back to this level’
