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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.
In a groundbreaking new report from Reuters, SpaceX is reportedly discussing merger possibilities with xAI ahead of the space exploration company’s plans to IPO later this year, in what would be a blockbuster move.
The outlet said it would combine rockets and Starlink satellites, as well as the X social media platform and AI project Grok under one roof. The report cites “a person briefed on the matter and two recent company filings seen by Reuters.”
Musk, nor SpaceX or xAI, have commented on the report, so, as of now, it is unconfirmed.
With that being said, the proposed merger would bring shares of xAI in exchange for shares of SpaceX. Both companies were registered in Nevada to expedite the transaction, according to the report.
On January 21, both entities were registered in Nevada. The report continues:
“One of them, a limited liability company, lists SpaceX and Bret Johnsen, the company’s chief financial officer, as managing members, while the other lists Johnsen as the company’s only officer, the filings show.”
The source also stated that some xAI executives could be given the option to receive cash in lieu of SpaceX stock. No agreement has been reached, nothing has been signed, and the timing and structure, as well as other important details, have not been finalized.
SpaceX is valued at $800 billion and is the most valuable privately held company, while xAI is valued at $230 billion as of November. SpaceX could be going public later this year, as Musk has said as recently as December that the company would offer its stock publicly.
The plans could help move along plans for large-scale data centers in space, something Musk has discussed on several occasions over the past few months.
At the World Economic Forum last week, Musk said:
“It’s a no-brainer for building solar-powered AI data centers in space, because as I mentioned, it’s also very cold in space. The net effect is that the lowest cost place to put AI will be space and that will be true within two to three years, three at the latest.”
He also said on X that “the most important thing in the next 3-4 years is data centers in space.”
If the report is true and the two companies end up coming together, it would not be the first time Musk’s companies have ended up coming together. He used Tesla stock to purchase SolarCity back in 2016. Last year, X became part of xAI in a share swap.
Tesla has announced it has hit a major milestone with Full Self-Driving subscriptions, shortly after it said it would exclusively offer the suite without the option to purchase it outright.
Tesla announced on Wednesday during its Q4 Earnings Call for 2025 that it had officially eclipsed the one million subscription mark for its Full Self-Driving suite. This represented a 38 percent increase year-over-year.
This is up from the roughly 800,000 active subscriptions it reported last year. The company has seen significant increases in FSD adoption over the past few years, as in 2021, it reported just 400,000. In 2022, it was up to 500,000 and, one year later, it had eclipsed 600,000.
NEWS: For the first time, Tesla has revealed how many people are subscribed or have purchased FSD (Supervised).
Active FSD Subscriptions:
• 2025: 1.1 million
• 2024: 800K
• 2023: 600K
• 2022: 500K
• 2021: 400K pic.twitter.com/KVtnyANWcs— Sawyer Merritt (@SawyerMerritt) January 28, 2026
In mid-January, CEO Elon Musk announced that the company would transition away from giving the option to purchase the Full Self-Driving suite outright, opting for the subscription program exclusively.
Musk said on X:
“Tesla will stop selling FSD after Feb 14. FSD will only be available as a monthly subscription thereafter.”
The move intends to streamline the Full Self-Driving purchase option, and gives Tesla more control over its revenue, and closes off the ability to buy it outright for a bargain when Musk has said its value could be close to $100,000 when it reaches full autonomy.
It also caters to Musk’s newest compensation package. One tranche requires Tesla to achieve 10 million active FSD subscriptions, and now that it has reached one million, it is already seeing some growth.
The strategy that Tesla will use to achieve this lofty goal is still under wraps. The most ideal solution would be to offer a less expensive version of the suite, which is not likely considering the company is increasing its capabilities, and it is becoming more robust.
Tesla is shifting FSD to a subscription-only model, confirms Elon Musk
Currently, Tesla’s FSD subscription price is $99 per month, but Musk said this price will increase, which seems counterintuitive to its goal of increasing the take rate. With that being said, it will be interesting to see what Tesla does to navigate growth while offering a robust FSD suite.
News
Tesla confirms Robotaxi expansion plans with new cities and aggressive timeline
Tesla plans to launch in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas. It lists the Bay Area as “Safety Driver,” and Austin as “Ramping Unsupervised.”
Tesla confirmed its intentions to expand the Robotaxi program in the United States with an aggressive timeline that aims to send the ride-hailing service to several large cities very soon.
The Robotaxi program is currently active in Austin, Texas, and the California Bay Area, but Tesla has received some approvals for testing in other areas of the U.S., although it has not launched in those areas quite yet.
However, the time is coming.
During Tesla’s Q4 Earnings Call last night, the company confirmed that it plans to expand the Robotaxi program aggressively, hoping to launch in seven new cities in the first half of the year.
Tesla plans to launch in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas. It lists the Bay Area as “Safety Driver,” and Austin as “Ramping Unsupervised.”
These details were released in the Earnings Shareholder Deck, which is published shortly before the Earnings Call:
🚨 BREAKING: Tesla plans to launch its Robotaxi service in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas in the first half of this year pic.twitter.com/aTnruz818v
— TESLARATI (@Teslarati) January 28, 2026
Late last year, Tesla revealed it had planned to launch Robotaxi in Las Vegas, Phoenix, Dallas, and Houston, but Tampa and Orlando were just added to the plans, signaling an even more aggressive expansion than originally planned.
Tesla feels extremely confident in its Robotaxi program, and that has been reiterated many times.
Although skeptics still remain hesitant to believe the prowess Tesla has seemingly proven in its development of an autonomous driving suite, the company has been operating a successful program in Austin and the Bay Area for months.
In fact, it announced it achieved nearly 700,000 paid Robotaxi miles since launching Robotaxi last June.
🚨 Tesla has achieved nearly 700,000 paid Robotaxi miles since launching in June of last year pic.twitter.com/E8ldSW36La
— TESLARATI (@Teslarati) January 28, 2026
With the expansion, Tesla will be able to penetrate more of the ride-sharing market, disrupting the human-operated platforms like Uber and Lyft, which are usually more expensive and are dependent on availability.
Tesla launched driverless rides in Austin last week, but they’ve been few and far between, as the company is certainly easing into the program with a very cautiously optimistic attitude, aiming to prioritize safety.
SpaceX reportedly discussing merger with xAI ahead of blockbuster IPO
Tesla hits major milestone with Full Self-Driving subscriptions
