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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 Full Self-Driving (Supervised) has taken yet another significant step forward in Europe. On May 29, Estonia became the third European Union country to approve the advanced driver-assistance technology, following approvals in the Netherlands and Lithuania.
Tesla Europe announced the news on X, confirming the expansion has continued across the continent that, at one time, seemed to be taking its sweet old time giving any approval to the FSD suite.
FSD Supervised now approved in Estonia🇪🇪. Rollout will begin soon pic.twitter.com/y5a64qlp5m
— Tesla Europe, Middle East & Africa (@teslaeurope) May 29, 2026
Estonia’s Transport Administration (Transpordiamet) granted the approval by recognizing the type certification issued by the Dutch vehicle authority RDW. This mutual recognition mechanism, enabled by EU regulations, allows other member states to fast-track deployment without repeating extensive local testing.
The Estonian authority noted that Tesla’s FSD had undergone rigorous evaluation on European roads for approximately 18 months before the initial Dutch approval in April 2026.
FSD Supervised remains classified as a Level 2 advanced driver-assistance system (ADAS). Drivers must maintain full attention, keep their hands on the wheel, and stay ready to intervene at any moment.
The system assists with tasks such as automatic lane changes, navigation through city streets, and responding to traffic objects, but it does not constitute full autonomy. Estonian officials emphasized this distinction, underscoring that safety responsibility lies entirely with the driver.
The rapid progression across the Baltic region highlights Tesla’s strategic approach to European expansion. The Netherlands provided the foundational type approval in April, unlocking doors for neighboring countries.
Lithuania followed swiftly in mid-May, with rollout beginning shortly thereafter. Estonia’s decision, coming just days later, demonstrates how smaller, digitally progressive nations are accelerating adoption.
Tesla owners in Estonia can expect an over-the-air software update in the coming weeks, bringing the latest FSD capabilities to compatible vehicles
This expansion builds on Tesla’s global momentum. FSD Supervised is now available in 11 countries worldwide, including the United States, Canada, Australia, and South Korea. In Europe, the approvals signal growing regulatory confidence in Tesla’s vision-based AI approach, which relies on cameras and neural networks rather than lidar or radar-heavy alternatives used by some competitors.
For Tesla, these European milestones are more than symbolic. They validate years of data collection and software iteration while opening new revenue streams through FSD subscriptions and purchases.
As the company continues refining its AI models with real-world miles from diverse driving environments, including Estonia’s variable winter conditions, the dataset grows richer, potentially benefiting global users.
Elon Musk has firmly denied recent media reports suggesting that SpaceX has reduced its target valuation for an upcoming initial public offering.
The denial came directly from the SpaceX and Tesla frontman on his social media platform X, where he responded with a single word, “False,” to a post from ZeroHedge that cited Bloomberg sources.
This swift rebuttal underscores Musk’s ongoing effort to manage speculation surrounding one of the most anticipated market debuts in recent history.
False
— Elon Musk (@elonmusk) May 29, 2026
According to the disputed reports, SpaceX had lowered its IPO valuation goal to at least $1.8 trillion from previous ambitions exceeding $2 trillion.
The claims emerged amid growing anticipation for the company’s confidential S-1 filing, which positions it for a potential public listing as early as June.
Some had pointed to strong revenue growth, particularly from the Starlink satellite internet service, which contributed heavily to the firm’s 2025 figures of $18.7 billion. Yet challenges persist in other areas, including substantial investments and losses tied to ambitious projects like Starship development and artificial intelligence initiatives, which plan to make life multiplanetary eventually.
Musk’s response highlights a pattern in which he actively counters what he views as inaccurate portrayals of his companies’ trajectories.
SpaceX, already valued privately at extraordinary levels, stands as a cornerstone of Musk’s empire alongside Tesla and xAI. The entrepreneur has long emphasized the transformative potential of reusable rockets and global broadband access, factors that fuel investor enthusiasm despite operational hurdles.
By rejecting the valuation downgrade narrative, Musk signals confidence in SpaceX’s fundamentals and its readiness for public markets on terms favorable to its long-term vision. People have been waiting a very long time to invest in SpaceX, and the valuation, as well as the introductory share price, is not going to need adjusting.
They’ll have plenty of suitors.
This episode reflects broader dynamics in the technology sector, where rumors often swirl around high-profile entities. Musk’s direct engagement with media narratives serves to maintain transparency and control the narrative around his ventures.
As SpaceX prepares for greater scrutiny in public markets, the founder’s denial reinforces optimism about its prospects. Supporters argue that the company’s innovative edge positions it for enduring success, far beyond short-term valuation debates. With the denial now public, attention turns to forthcoming regulatory filings that could provide clearer insights into SpaceX’s strategy and financial health.
The coming weeks promise to reveal more about how SpaceX will transition into a publicly traded powerhouse.
Tesla’s dreams of operating a fully autonomous ride-hailing platform just took a massive step toward reality, as two separate events have indicated the company is perhaps closer than ever to achieving self-driving as a product.
On Thursday, Tesla was granted authorization by the State of Texas to operate driverless vehicles in a commercial manner. On May 28, Senate Bill 2807, passed by the 89th Texas Legislature, took effect after being passed back on September 1, 2025.
The bill establishes a statewide regulatory framework requiring authorization from the Texas Department of Motor Vehicles for companies to operate automated vehicles commercially on Texas roads.
This covers driverless, or SAE Level 4+, operations for passenger transport, meaning Robotaxi, or freight.
Tesla and other companies can self-certify their vehicles and tech as long as they:
- Operate in compliance with Texas traffic laws
- Maintain proper registration, title, and insurance
- Use compliant automated driving systems
- Record onboard activity and handle system failures and glitches safely.
The new authorization, which was first reported by James Stephenson on X, allows companies to utilize their own processes to determine if their vehicles are ready to operate without drivers.
🚨BREAKING:
Tesla has been authorized by the State of Texas to operate driverless vehicles commercially under the new law that took effect today, May 28th, 2026. Tesla has officially self-certified the software running on its robotaxis as Level 4. $TSLA pic.twitter.com/KSJdsvlaW5— James Stephenson (@ICannot_Enough) May 28, 2026
It is a rule that expedites the entire approval process, keeping agencies out of a usually long, lengthy, and frustrating task that is essential to technological advancements. It essentially means Tesla can launch commercial Robotaxi operations at this point.
On the very same day, Tesla continued the momentum as CEO Elon Musk shared a video of Cybercab units autonomously driving off the property at Gigafactory Texas. This is a major step in the story of the Cybercab.
Mass production of the Cybercab started at Giga Texas in April, and it is already heading out of the factory on its own.
Cybercab driving itself out of the GigaTexas factory pic.twitter.com/EwAMVVDjYy
— Elon Musk (@elonmusk) May 28, 2026
These two major events mark a drastic step forward in Tesla’s progress toward Cybercab and the permissions it needs to operate a self-driving ride-hailing service. Tesla is now able to operate autonomously under Texas law by self-certifying, and with the potentially imminent rollout of Cybercab, Tesla’s autonomous dreams are starting to take serious shape.
Tesla Full Self-Driving expansion in Europe continues with new addition
Elon Musk strikes down reports on SpaceX IPO rumors
