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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.
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Tesla says its Texas lithium refinery is now operational and unlike anything in North America
Elon Musk separately described the site as both the most advanced and the largest lithium refinery in the United States.
Tesla has confirmed that its Texas lithium refinery is now operational, marking a major milestone for the company’s U.S. battery supply chain. In a newly released video, Tesla staff detailed how the facility converts raw spodumene ore directly into battery-grade lithium hydroxide, making it the first refinery of its kind in North America.
Elon Musk separately described the site as both the most advanced and the largest lithium refinery in the United States.
A first-of-its-kind lithium refining process
In the video, Tesla staff at the Texas lithium refinery near Corpus Christi explained that the facility processes spodumene, a lithium-rich hard-rock ore, directly into battery-grade lithium hydroxide on site. The approach bypasses intermediate refining steps commonly used elsewhere in the industry.
According to the staff, spodumene is processed through kilns and cooling systems before undergoing alkaline leaching, purification, and crystallization. The resulting lithium hydroxide is suitable for use in batteries for energy storage and electric vehicles. Tesla employees noted that the process is simpler and less expensive than traditional refining methods.
Staff at the facility added that the process eliminates hazardous byproducts typically associated with lithium refining. “Our process is more sustainable than traditional methods and eliminates hazardous byproducts, and instead produces a co-product named anhydrite, used in concrete mixes,” an employee noted.
Musk calls the facility the largest lithium refinery in America
The refinery’s development timeline has been very impressive. The project moved from breaking ground in 2023 to integrated plant startup in 2025 by running feasibility studies, design, and construction in parallel. This compressed schedule enabled the fastest time-to-market for a refinery using this type of technology. This 2026, the facility has become operational.
Elon Musk echoed the significance of the project in posts on X, stating that “the largest Lithium refinery in America is now operational.” In a separate comment, Musk described the site as “the most advanced lithium refinery in the world” and emphasized that the facility is “very clean.”
By bringing large-scale lithium hydroxide production online in Texas, Tesla is positioning itself to reduce reliance on foreign refining capacity while supporting its growth in battery and vehicle production. The refinery also complements Tesla’s nascent domestic battery manufacturing efforts, which could very well be a difference maker in the market.
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Tesla Optimus V3 gets early third-party feedback, and it’s eye-opening
Jason Calacanis’ remarks, which were shared during a discussion at CES 2026, offered one of the first third-party impressions of the yet-to-be-unveiled robot
Angel investor and entrepreneur Jason Calacanis shared some insights after he got an early look at Tesla’s upcoming Optimus V3. His remarks, which were shared during a discussion at CES 2026, offered one of the first third-party impressions of the yet-to-be-unveiled robot.
Calacanis’ comments were shared publicly on X, and they were quite noteworthy.
The angel investor stated that he visited Tesla’s Optimus lab on a Sunday morning and observed that the place was buzzing with energy. The investor then shared a rare, shocking insight. As per Calacanis, Optimus V3 will be so revolutionary that people will probably not even remember that Tesla used to make cars in the future.
“I don’t want to name drop, but two Sundays ago, I went to Tesla with Elon and I went and visited the Optimus lab. There were a large number of people working on a Sunday at 10 a.m. and I saw Optimus 3. I can tell you now, nobody will remember that Tesla ever made a car,” he noted.
The angel investor also reiterated the primary advantage of Optimus, and how it could effectively change the world.
“They will only remember the Optimus and that he is going to make a billion of those, and it is going to be the most transformative technology product ever made in the history of humanity, because what LLMs are gonna enable those products to do is understand the world and then do things in the world that we don’t want to do. I believe there will be a 1:1 ratio of humans to Optimus, and I think he’s already won,” he said.
While Calacanis’ comments were clearly opinion-driven, they stood out as among the first from a non-Tesla employee about Optimus V3. Considering his reaction to the humanoid robot, perhaps Elon Musk’s predictions for Optimus V3 might not be too far-fetched at all.
Tesla has been careful with its public messaging around Optimus V3’s development stage. Musk has previously stated on X that Optimus V3 has not yet been revealed publicly, clarifying that images and videos of the robot online still show Optimus V2 and V2.5, not the next-generation unit. As for Calacanis’ recent comments, however, Musk responded with a simple “Probably true” in a post on X.
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Tesla taps Samsung for 5G modems amid plans of Robotaxi ramp: report
The move signals Tesla’s growing focus on supply-chain diversification and next-generation communications as it prepares to scale its autonomous driving and robotaxi operations.
A report from South Korea has suggested that Samsung Electronics is set to begin supplying 5G automotive modems to Tesla. If accurate, this would mark a major expansion of the two companies’ partnership beyond AI chips and into vehicle connectivity.
The move signals Tesla’s growing focus on supply-chain diversification and next-generation communications as it prepares to scale its autonomous driving and Robotaxi operations.
Samsung’s 5G modem
As per industry sources cited by TheElec, Samsung’s System LSI division has completed development of a dedicated automotive-grade 5G modem for Tesla. The 5G modem is reportedly in its testing phase. Initial supply is expected to begin in the first half of this year, with the first deployments planned for Tesla’s Robotaxi fleet in Texas. A wider rollout to consumer vehicles is expected to follow.
Development of the modem began in early 2024 and it required a separate engineering process from Samsung’s smartphone modems. Automotive modems must meet stricter durability standards, including resistance to extreme temperatures and vibration, along with reliability over a service life exceeding 10 years. Samsung will handle chip design internally, while a partner company would reportedly manage module integration.
The deal represents the first time Samsung has supplied Tesla with a 5G vehicle modem. Tesla has historically relied on Qualcomm for automotive connectivity, but the new agreement suggests that the electric vehicle maker may be putting in some serious effort into diversifying its suppliers as connectivity becomes more critical to autonomous driving.
Deepening Tesla–Samsung ties
The modem supply builds on a rapidly expanding relationship between the two companies. Tesla previously selected Samsung’s foundry business to manufacture its next-generation AI6 chips, a deal valued at more than 22.7 trillion won and announced in mid-2025. Together, the AI chip and 5G modem agreements position Samsung as a key semiconductor partner for Tesla’s future vehicle platforms.
Industry observers have stated that the collaboration aligns with Tesla’s broader effort to reduce reliance on Chinese and Taiwanese suppliers. Geopolitical risk and long-term supply stability are believed to be driving the shift in no small part, particularly as Tesla prepares for large-scale Robotaxi deployment.
Stable, high-speed connectivity is essential for Tesla’s Full Self-Driving system, supporting real-time mapping, fleet management, and continuous software updates. By pairing in-vehicle AI computing with a new 5G modem supplier, Tesla appears to be tightening control over both its hardware stack and its global supply chain.
Tesla says its Texas lithium refinery is now operational and unlike anything in North America
Tesla Optimus V3 gets early third-party feedback, and it’s eye-opening
