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Stanford studies human impact when self-driving car returns control to driver

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Tesla Autopilot in 'Shadow Mode' will pit human vs computer

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.

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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.

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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.

"I write about technology and the coming zero emissions revolution."

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Elon Musk

Elon Musk shuts down talk of TSMC taking over Terafab

Musk says Tesla and SpaceX will build and run Terafab, with TSMC limited to renting.

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SpaceX Terafab rendering

Elon Musk has drawn a firm line around who will be in charge of Terafab, the giant chip factory Tesla and SpaceX are planning in Texas.

Musk replied to a post on X arguing that Taiwan Semiconductor Manufacturing Company (TSMC) would most likely end up owning and operating the plant. “No, we will build and run the fab. Let there be ZERO doubt about that,” Musk wrote. “Maybe TSMC subleases part of the Terafab if they want, but nothing more than that.”

In plain terms, a sublease means TSMC could rent a section of the complex to make chips, similar to a tenant renting one floor of an office tower. The building, the equipment decisions and the daily operation would stay with Tesla and SpaceX.

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The comment shuts down speculation that started last week. On October 2, tech journalist Tim Culpan reported that TSMC was exploring ways to help run Terafab’s factories. Musk responded the next day that it was “just discussions, but something may come of it,” as Teslarati reported at the time. That left room for a scenario where the world’s largest contract chipmaker took the wheel. Musk’s latest post closes that door.

Elon Musk teases TSMC as potential Terafab partner

Some background helps explain why this matters. Tesla designs its own AI chips today but pays outside companies like TSMC and Samsung to manufacture them. Musk unveiled Terafab in March as a joint project between Tesla, SpaceX and xAI, arguing that existing suppliers cannot expand fast enough to meet his companies’ future demand. The goal is to produce enough chips each year to supply one terawatt of computing power, roughly 50 times what the entire global AI chip industry produces now.

Those chips are meant for Tesla’s Optimus humanoid robots, the Cybercab and Full Self-Driving computers, along with chips for SpaceX’s planned data centers in orbit. Owning the factory means Musk’s companies would not have to compete with every other chip customer for time on someone else’s production lines.

Intel is still part of the picture. The company signed on in April to help design, build and package chips for the project, and CEO Lip-Bu Tan told Bloomberg this week that Intel will keep working on Terafab despite the TSMC chatter.

The project moved from concept to construction planning over the summer. In August, SpaceX confirmed the Grimes County site about an hour from Houston, sent the county a $10 million payment under its tax abatement deal and said civil work would begin shortly. The first phase carries a $16.8 billion price tag, and total spending across all phases could reach as much as $119 billion.

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TSMC chairman C.C. Wei has said a new fab typically takes two to three years to build and another one to two years to reach full output. Tesla and SpaceX have never run one, which is why TSMC’s expertise drew so much attention. Musk’s answer suggests he would rather learn that process in house than hand control of a project this central to Tesla’s robotics and autonomy plans to an outside company.

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Elon Musk

Trump to hand Elon Musk a top honor that traces back to JFK

Trump will award Elon Musk the National Medal of Science at Thursday’s White House summit.

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elon musk and donald trump in front of a tesla cybertruck at the white house

Elon Musk is set to receive the highest honor the U.S. government gives to scientists and engineers.

President Donald Trump will present Musk with the National Medal of Science on Thursday at the White House’s Science: A New Golden Age Summit, Fox News Digital first reported on Wednesday. Google cofounder Sergey Brin, Nvidia CEO Jensen Huang and AMD CEO Lisa Su will receive the same medal, while Dell Technologies CEO Michael Dell and Microsoft CEO Satya Nadella will receive the National Medal of Technology and Innovation. A White House official later confirmed the list to Reuters.

“The Trump administration is grateful for the contributions of these incredible leaders in science and technology. These recipients are helping ensure America keeps leading the world in innovation,” White House spokesperson Liz Huston told Fox News.

It will be the first time Trump has presented either medal in his two terms. Congress created the National Medal of Science in 1959, and the National Science Foundation, which administers it, says 529 scientists and engineers have received it since. A presidential committee reviews nominees, but the president makes the final call.

Thursday’s group of medalists run or founded companies, and three of them sit at the center of the Super Intelligence hardware race that Musk competes in. Huang’s Nvidia supplies the GB300 chips filling SpaceX’s Colossus 2 cluster, while Su’s AMD is Nvidia’s biggest rival in data center GPUs.

Worth noting that Trump’s uncle, MIT physicist John G. Trump, received the National Medal of Science from President Ronald Reagan for his work on ionizing radiation and its uses in medicine and industry.

The Pentagon taps Elon Musk to design the battlefield of the future

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For Musk, the medal is the latest sign of how far his relationship with Trump has come since their 2025 split over the “Big Beautiful Bill” and his exit from DOGE. Last week, he sat at Trump’s left during a White House lunch where AI executives signed a voluntary safety accord, and Defense Secretary Pete Hegseth named him to help lead the Pentagon’s Project Meridian study on the future of warfare. Musk has also adopted the administration’s new vocabulary, saying on Sunday that SpaceXAI will be renamed SpaceXSI after Trump ordered federal agencies to replace “artificial intelligence” with “super intelligence.”

Musk has collected science honors before, including the Stephen Hawking Medal for Science Communication in 2019.

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Tesla FSD changed its mind mid-intersection, and it may have saved a life

Tesla shares dashcam footage of FSD Supervised stopping mid intersection to avoid a T-bone crash.

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Credit: @BLKMDL3/X

Tesla is putting another Full Self-Driving save in front of its 24.8 million followers on X.

On Tuesday morning, Tesla’s main account shared a dashcam clip with the caption “FSD Supervised preventing T-bone crash.” The footage came from an owner posting as TheNewGrid, who described what happened at a stop sign: “I looked at the car coming to the stop sign figured they would stop, my car went, then came to a stop mid intersection as they flew by. Had I been manually driving this would have resulted in a crash.”

The sequence is the notable part. FSD had already started crossing when the other driver ran the stop sign. Instead of pressing on, the car braked hard in the middle of the intersection and let the crossing vehicle pass in front of it. By the owner’s own account, they had made the same assumption the software initially made, that the other car would stop, and would not have corrected in time.

The clip is the latest in a run of safety posts Tesla has amplified over the past several days. On Saturday, the company shared a video from Selling Sunset star Jason Oppenheim, who sold his Bentley for a Model Y and said he was buying Teslas with FSD for 10 of his employees. Ashok Elluswamy, who leads Tesla AI, followed up by writing that Tesla self-driving “reacts to other people cutting into your path with super-human response times.” On Monday, a Cybertruck owner posted footage of FSD moving across three lanes from a red light to clear a path for an ambulance approaching from behind.

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This recent clip also lands a few weeks after Tesla began shipping Automatic Collision Evasion with FSD v14.3.9, a feature that can activate FSD on the driver’s behalf when a frontal collision is imminent or the driver appears distracted. Elluswamy said in September that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” are coming with v15, the release Tesla has tied to round the clock Robotaxi operation.

The safety messaging matters beyond social media. Tesla has said FSD Supervised was 4.1 times less likely to crash than manual driving across 100 million kilometers on European roads, and it has been putting those figures in front of regulators. Eight EU countries have now approved FSD Supervised, with Croatia the most recent, but the EU’s bloc-wide vote originally set for October 6 has been pushed to December at the earliest.

FSD Supervised is still a Level 2 system, and the driver remains responsible at all times. Even heavy users find reasons to step in. Teslarati’s Joey Klender, who uses FSD for about 76 percent of his driving, laid out five recurring issues on Tuesday that still prompt him to intervene. Clips like this one show the other column of that ledger: moments where the software caught a mistake a human was about to make.

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