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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.
SpaceX has decided to stand down from what was supposed to be the first test launch of Starship’s v3 rocket tonight after a minor issue with a hydraulic pin delayed the flight once more.
The company scrubbed its first test flight of the upgraded Starship v3 on May 21 in the final minutes of the countdown. SpaceX CEO Elon Musk quickly took to social media platform X, explaining that a hydraulic pin on the launch tower’s “chopsticks” arm failed to retract properly.
Musk added that the company would fix the issue this evening. SpaceX will attempt another launch tomorrow night at 5:30 p.m. CT, 6:30 p.m. ET, and 3:30 p.m. PT.
The hydraulic pin holding the tower arm in place did not retract.
If that can be fixed tonight, there will be another launch attempt tomorrow at 5:30 CT. https://t.co/DJAdvDYQpH
— Elon Musk (@elonmusk) May 21, 2026
The countdown for Starship Flight 12 — featuring the taller and more capable V3 stack with Booster 19 and Ship 39 — had been progressing smoothly until the late-stage issue surfaced. The Mechazilla tower arm, designed to secure the vehicle on the pad and eventually catch returning boosters, could not complete its retraction sequence.
SpaceX teams immediately began troubleshooting the hydraulic system for an overnight repair.
Starship V3 introduces several significant upgrades over earlier versions. These include greater propellant capacity, more powerful Raptor 3 engines, larger grid fins, enhanced heat shielding, and an improved fuel transfer system.
We covered the changes that were announced just days ago by SpaceX:
SpaceX unveils sweeping Starship V3 upgrades ahead of May 19 launch
The changes are intended to increase payload performance, support higher flight rates, and advance the vehicle toward operational missions, including Starlink deployments, NASA Artemis lunar landings, and future crewed Mars flights. The debut flight from Starbase’s new Launch Pad 2 marked an important milestone in scaling up the fully reusable Starship system.
This stand-down highlights the intricate challenges of preparing the world’s most powerful rocket for flight. Despite extensive pre-launch checks, a single component in the ground support equipment can force a scrub.
The incident aligns with Starship’s proven iterative development approach. Previous test flights have encountered both successes and setbacks, each providing critical data that refines hardware and procedures. Some outlets may call some of these flights “failures,” when in reality, they are all opportunities for SpaceX to learn for the next attempt.
With V3, SpaceX aims to reduce ground-system dependencies and increase launch cadence to meet ambitious long-term goals.
The Tesla Model Y became the first-ever car to reach a legendary Norwegian milestone, surpassing 100,000 new registrations after gaining a reputation as one of the most popular vehicles in the country and the world.
As of May 20, Norwegian authorities have registered 100,224 units of the electric SUV, according to data from local outlet Opplysningsrådet for veitrafikken (OFV).
By population, roughly one in every 29 passenger cars on Norwegian roads is now a Model Y, underscoring its rapid rise as a national favorite.
Since the first deliveries in August 2021, the Model Y has transformed from a newcomer to a staple in Norwegian traffic.
Tesla back on top as Norway’s EV market surges to 98% share in February
Geir Inge Stokke, the Managing Director of OFV, described the achievement as “remarkable,” noting that few single models have gained such traction so quickly. “Tesla Model Y has hit the Norwegian market spot on, and the numbers illustrate how fast the EV market has developed here,” Stokke said.
The Model Y’s success reflects Norway’s aggressive push toward electrification. Nearly nine out of ten units, 87.6 percent, to be exact, are privately registered, with the remaining 12.4 percent on company plates. Owners span the country, from major cities to smaller municipalities, proving it is no longer just an urban or niche vehicle but a true “people’s car.
Who is Buying Tesla Model Ys in Norway?
Typical Model Y drivers are men in their early 40s. The average registered user age is 44, with 83 percent male and 17 percent female. Stokke noted that household usage often extends beyond the primary registrant, broadening the vehicle’s real-world appeal.
Geographically, adoption concentrates in urban centers with strong charging infrastructure. Oslo leads with 16,861 registrations (16.82 percent of the national total), followed by Bergen (7,450), Bærum (4,313), and Trondheim (4,240).
The top five municipalities—Oslo, Bergen, Bærum, Trondheim, and Asker—account for 35,463 units, or about 35 percent of all Model Ys. Yet the vehicle’s presence outside big cities highlights its broad acceptance.
Growth Trajectory and Popularity
Tesla built a lot of sales momentum in a short amount of time. In 2021, registrations closed out at 8,267, but more than doubled to more than 17,000 units in 2022 and more than 23,000 units in 2023. 2025 was the company’s strongest year yet, as Tesla managed to record 27,621 registrations.
Through 2026, Tesla already has 7,036 registrations.
Tesla’s Global Success with the Model Y
Tesla has tasted so much success with the Model Y; it has been the best-selling car in the world three times, it has dominated EV sales in numerous countries, and contributed to a mass adoption of electric vehicles across the planet.
As Stokke emphasized, the Model Y’s journey from newcomer to icon mirrors Norway’s broader success story. With robust incentives that push sales, excellent infrastructure, and consumer eagerness to transition to sustainable powertrains, the country continues setting global benchmarks in sustainable mobility.
The Tesla Model Y stands as a shining example of how quickly change can happen when conditions align.
SpaceX has disclosed the full financial details of its groundbreaking agreement with Anthropic, confirming that the AI company will pay $1.25 billion per month for dedicated high-performance computing resources.
The revelation came through SpaceX’s latest securities filing in preparation for its initial public offering, shedding light on one of the largest compute deals in the artificial intelligence sector to date. The prospectus was released last night, as SpaceX is heading toward its IPO.
This arrangement underscores the fierce demand for specialized infrastructure as frontier AI models require unprecedented levels of processing power to train and operate effectively. Industry analysts see the disclosure as a significant milestone, highlighting how top AI labs are locking in massive capacity to stay ahead in a rapidly accelerating field.
For SpaceX, it feels like a massive move that pushes its perception as a company from space exploration to artificial intelligence.
SpaceX is following in Tesla’s footsteps in a way nobody expected
The comprehensive deal grants Anthropic exclusive access to SpaceX’s Colossus clusters, encompassing Colossus I and the substantially expanded Colossus II, which together deliver hundreds of megawatts of power along with more than 200,000 NVIDIA GPUs.
Payments extend through May 2029, totaling nearly $45 billion overall; capacity is scheduled to ramp up during May and June 2026 at an initial discounted rate to facilitate seamless integration. Both companies retain the option to terminate the agreement with ninety days’ notice, so there is definitely some flexibility for both.
This pact not only enhances Anthropic’s ability to scale usage limits for Claude users but also injects substantial recurring revenue into SpaceX, bolstering its expansion into advanced data center operations and future orbital computing initiatives.
Observers describe the collaboration between the two companies as strategically advantageous because it gives Anthropic cutting-edge AI development the opportunity to collaborate with SpaceX’s expertise in rapid, large-scale infrastructure deployment.
This disclosure arrives at a pivotal moment when computing resources have become the primary bottleneck for AI progress.
As leading organizations compete to build more powerful systems, securing reliable, high-density facilities has emerged as a key differentiator.
SpaceX’s sites, such as those in Memphis, offer superior power availability and advanced cooling solutions that set them apart from conventional providers. For Anthropic, the added capacity is expected to deliver tangible improvements, including extended context windows, quicker inference times, and innovative features that appeal to both enterprise clients and individual users.
Looking ahead, the partnership paves the way for ambitious joint projects, including potential space-based AI compute platforms designed to overcome terrestrial limitations on energy and thermal management. Such efforts could redefine sustainable computing at massive scales.
Financially, the deal solidifies SpaceX’s diverse revenue profile ahead of its public market debut, extending beyond traditional aerospace activities. The massive check SpaceX will cash each month opens up the idea that additional
While some experts question the sustainability of these enormous expenditures given ongoing efficiency gains in AI architectures, the commitment reflects a strong belief in sustained demand growth.
The agreement also exemplifies productive synergies across sectors, with aerospace engineering insights optimizing AI hardware performance. As global attention on technology concentration increases, arrangements of this nature may help shape equitable access to critical resources.
SpaceX reveals reason for Starship v3 stand down, announces next launch date
Tesla Model Y becomes first-ever car to reach legendary milestone
