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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 (NASDAQ: TSLA) is set to hold its Earnings Call for the first quarter of 2026 on Wednesday, and there are a lot of interesting things that are swirling around in terms of speculation from investors.
With the company’s executives, including CEO Elon Musk, answering a handful of questions that investors submit through the Say platform, fans want to know a lot of things about a lot of things.
These five questions come from Retail Investors, who are normal, everyday shareholders:
- When will we have the Optimus v3 reveal? When will Optimus production start, since we ended the Model S and Model X production earlier than mid-year? What’s the expected Optimus production rate exiting this year? What are the initial targeted skills?
- What milestones are you targeting for unsupervised FSD and Robotaxi expansion beyond Austin this year, and how will that drive recurring revenue?
- How will Hardware 3 cars reach Unsupervised Full Self-Driving?
- When do you expect Unsupervised Full Self-Driving to reach customer cars?
- When will Robotaxi expand past its current limited rollout?
Additionally, these are currently the three questions that are slated to be answered by Institutional Firms, which also answer a handful of questions during the call:
- Now that FSD has been approved in the Netherlands and is expected to launch across Europe this summer, can you discuss your Robotaxi strategy for the region?
- What enabled you to finish the AI5 tapeout early and were there any changes to the original vision? Last week, Elon said AI5 will go into Optimus and the Supercomputer, but one month ago said it would go into the Robotaxi. Has AI5 been dropped from the vehicle roadmap?
- Given the recent NHTSA incident filings, can you update us on the Robotaxi safety data? If safety validation remains the primary bottleneck, why not deploy thousands of vehicles to accelerate the removal of the safety driver?
The questions range through every current Tesla project, including FSD expansion and Optimus. However, many of the answers we will get will likely be repetitive answers we’ve heard in the past.
This is especially pertinent when the questions about when Unsupervised FSD will reach customer cars: we know Musk will say that it will happen this year. Is Tesla capable of that? Maybe. But a more transparent answer that is more revealing of a true timeline would be appreciated.
Hardware 3 owners are anxiously awaiting the arrival of FSD v14 Lite, which was promised to them last year for a release sometime this year.
The Earnings Call is set to take place on Wednesday at market close.
Elon Musk
Elon Musk reveals shocking Tesla Optimus patent detail
What looked promising on paper and in simulations failed to deliver the reliability required for a robot expected to handle delicate tasks like folding laundry, assembling electronics, or assisting in factories and homes.
Elon Musk revealed a shocking detail on the Tesla Optimus patent that was revealed last week. Despite it being made public for the first time, Musk said the company has already moved on from the design, an incredible truth about the development of new technology: things move fast.
Musk dropped a bombshell about the Tesla Optimus humanoid robot hand patent that was released last week. Musk, candidly replying to a post late at night on X, revealed that what is a new technology to many fans and insiders is actually old news to those developing the tech directly.
“We already changed the design,” Musk said. “This one didn’t actually work.”
We already changed the design. This one didn’t actually work.
— Elon Musk (@elonmusk) April 19, 2026
Patents, after all, are often viewed as blueprints for future products. Yet Musk revealed that the rolling contact mechanism—intended to provide smooth, low-friction articulation in the fingers—had already been scrapped after real-world testing exposed its shortcomings.
What looked promising on paper and in simulations failed to deliver the reliability required for a robot expected to handle delicate tasks like folding laundry, assembling electronics, or assisting in factories and homes.
The hand has been one of the biggest challenges for Tesla engineers since Optimus development started years ago. Musk has said that there is not enough recognition for how incredible and useful the human hand is, and designing one for a humanoid robot has been the biggest challenge of all.
Tesla is stumped on how to engineer this Optimus part, but they’re close
This moment underscores the persistent engineering hurdles in achieving reliable humanoid hand dexterity. Human fingers are marvels of evolution: 27 bones, intricate tendons, ligaments, and a network of sensors working in perfect harmony. Replicating that in metal and silicon is extraordinarily difficult.
Rolling contacts promised reduced wear and precise motion, but testing likely revealed issues with durability under repeated stress, grip stability on varied surfaces, or the micro-precision needed for fine motor skills.
These aren’t minor tweaks, but instead they represent fundamental challenges that have plagued robotics teams for decades. Even advanced competitors struggle here—hands remain the Achilles’ heel of most humanoids because the margin for error is razor-thin.
A fraction of a millimeter off, and a robot drops a glass or fails to button a shirt.
What makes Musk’s reply remarkable is how it signals Tesla’s direct communication style on prototype limitations. While many companies guard failures behind glossy marketing and vague timelines, Tesla openly shares setbacks.
Musk was forthcoming about the failure of this recent design. This transparency builds trust with investors, engineers, and fans. It shows Tesla treats Optimus development like true science: rapid iteration, rigorous testing, and zero tolerance for hype that doesn’t match reality.
The disclosure from Musk also highlights Tesla’s blistering pace of development. By the time the patents are published, which is often over a year after the initial filing, the technology has already evolved.
Optimus is far from a static product, and it’s a living project advancing weekly.
In the high-stakes race for general-purpose robots, Tesla’s approach stands out. Admitting a finger-joint design “didn’t actually work” isn’t a weakness—it’s confidence.
True innovation demands confronting failure head-on, and Musk just reminded the world that Optimus is being engineered that way. The next version of those hands is already in testing, and it will be better because Tesla isn’t afraid to say what didn’t work.
Elon Musk
Tesla is sending its humanoid Optimus robot to the Boston Marathon
Tesla’s Optimus robot is heading to the Boston Marathon finish line
Tesla’s Optimus humanoid robot will be stationed at the Tesla showroom at 888 Boylston Street in Boston, right along the final stretch of the Boston Marathon today, ready to cheer on runners and pose for photos with spectators.
According to a Tesla email shared by content creator Sawyer Merritt on X, Optimus will be at the Boston Boylston Street showroom on April 20, coinciding with Marathon Monday weekend. The Boston Marathon finishes on Boylston Street, and the surrounding area draws hundreds of thousands of spectators along with international broadcast coverage. Placing Optimus there puts it in front of a massive public audience at zero advertising cost.
Just got this email. @Tesla’s Optimus robot is coming to Boston.
“Join us from April 19 to 20, 2026, at Tesla Boston Boylston Street showroom to meet Optimus, our humanoid robot, for Marathon Monday. Optimus will be cheering with you on the sidelines and posing for photos.” pic.twitter.com/chxoooO2xV
— Sawyer Merritt (@SawyerMerritt) April 18, 2026
The Tesla showroom is at 888 Boylston Street, between Gloucester Street and Fairfield Street. The final mile of the marathon runs directly along Boylston Street, with runners passing the big stores before reaching the finish line at Copley Square.
Optimus was first announced at Tesla’s AI Day event on August 19, 2021, when Elon Musk presented a vision for a general-purpose robot designed to take on dangerous, repetitive, and unwanted tasks. In March 2026, Optimus appeared at the Appliance and Electronics World Expo in Shanghai, where on-site staff stated that mass production of the robot could begin by the end of 2026. Before that, it showed up at the Tesla Hollywood Diner opening in July 2025 and at a Miami showroom event in December 2025.
Tesla’s well-calculated display of Optimus gives the public a low-pressure first encounter with a robot that Tesla is preparing to soon deploy at scale. The company has previously indicated plans to manufacture Optimus robots at its Fremont facility at up to 1 million units annually, with an Optimus production line at Gigafactory Texas targeting 10 million units per year.
Tesla showcases Optimus humanoid robot at AWE 2026 in Shanghai
Musk has said that Optimus “has the potential to be more significant than the vehicle business over time,” and separately that roughly 80 percent of Tesla’s future value will come from the robot program. Whether that holds depends on production execution. For now, Boston gets a preview of what that future looks like, standing at the finish line on Boylston Street while 32,000 runners pass by.
Tesla Q1 Earnings: What Elon Musk and Co. will answer during the call
Elon Musk reveals shocking Tesla Optimus patent detail
