News
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.
News
Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025.
The Tesla Model Y recorded the highest overall safety score of any vehicle tested by ANCAP in 2025. The Tesla Model 3 also delivered strong results, reinforcing the automaker’s safety leadership in Australia and New Zealand.
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025. ANCAP’s 2025 tests evaluated vehicles across four key pillars: Adult Occupant Protection, Child Occupant Protection, Vulnerable Road User Protection, and Safety Assist technologies.
The Model Y posted consistently strong results in all four categories, distinguishing itself through a system-based safety approach that combines structural crash protection with advanced driver-assistance features such as autonomous emergency braking, lane support, and driver monitoring.
This marked the second time the Model Y has topped ANCAP’s annual safety rankings. The Model Y’s previous version was also ANCAP’s top performer in 2022.
The Tesla Model 3 also delivered a strong performance in ANCAP’s 2025 tests, contributing to Tesla’s broader safety presence across segments. Similar to the Model Y, the Model 3 also earned impressive scores across the ANCAP’s four pillars. This made the vehicle the top performer in the Medium Car category.
ANCAP Chief Executive Officer Carla Hoorweg stated that the results highlight a growing industry shift toward integrated safety design, with improvements in technologies such as autonomous emergency braking and lane support translating into meaningful real-world protection.
“ANCAP’s testing continues to reinforce a clear message: the safest vehicles are those designed with safety as a system, not a checklist. The top performers this year delivered consistent results across physical crash protection, crash avoidance and vulnerable road user safety, rather than relying on strength in a single area.
“We are also seeing increasing alignment between ANCAP’s test requirements and the safety technologies that genuinely matter on Australian and New Zealand roads. Improvements in autonomous emergency braking, lane support, and driver monitoring systems are translating into more robust protection,” Hoorweg said.
News
Tesla Sweden uses Megapack battery to bypass unions’ Supercharger blockade
Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery.
Tesla Sweden has successfully launched a new Supercharger station despite an ongoing blockade by Swedish unions, using on-site Megapack batteries instead of traditional grid connections. The workaround has allowed the Supercharger to operate without direct access to Sweden’s electricity network, which has been effectively frozen by labor action.
Tesla has experienced notable challenges connecting its new charging stations to Sweden’s power grid due to industrial action led by Seko, a major Swedish trade union, which has blocked all new electrical connections for new Superchargers. On paper, this made the opening of new Supercharger sites almost impossible.
Despite the blockade, Tesla has continued to bring stations online. In Malmö and Södertälje, new Supercharger locations opened after grid operators E.ON and Telge Nät activated the sites. The operators later stated that the connections had been made in error.
More recently, however, Tesla adopted a different strategy altogether. Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery, as noted in a Dagens Arbete (DA) report.
Because the Supercharger station does not rely on a permanent grid connection, Tesla was able to bypass the blocked application process, as noted by Swedish car journalist and YouTuber Peter Esse. He noted that the Arlandastad Supercharger is likely dependent on nearby companies to recharge the batteries, likely through private arrangements.
Eight new charging stalls have been launched in the Arlandastad site so far, which is a fraction of the originally planned 40 chargers for the location. Still, the fact that Tesla Sweden was able to work around the unions’ efforts once more is impressive, especially since Superchargers are used even by non-Tesla EVs.
Esse noted that Tesla’s Megapack workaround is not as easily replicated in other locations. Arlandastad is unique because neighboring operators already have access to grid power, making it possible for Tesla to source electricity indirectly. Still, Esse noted that the unions’ blockades have not affected sales as much.
“Many want Tesla to lose sales due to the union blockades. But you have to remember that sales are falling from 2024, when Tesla sold a record number of cars in Sweden. That year, the unions also had blockades against Tesla. So for Tesla as a charging operator, it is devastating. But for Tesla as a car company, it does not matter in terms of sales volumes. People charge their cars where there is an opportunity, usually at home,” Esse noted.
Elon Musk
Elon Musk’s X goes down as users report major outage Friday morning
Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.
Elon Musk’s X experienced an outage Friday morning, leaving large numbers of users unable to access the social media platform.
Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.
Downdetector reports
Users attempting to open X were met with messages such as “Something went wrong. Try reloading,” often followed by an endless spinning icon that prevented access, according to a report from Variety. Downdetector data showed that reports of problems surged rapidly throughout the morning.
As of 10:52 a.m. ET, more than 100,000 users had reported issues with X. The data indicated that 56% of complaints were tied to the mobile app, while 33% were related to the website and roughly 10% cited server connection problems. The disruption appeared to begin around 10:10 a.m. ET, briefly eased around 10:35 a.m., and then returned minutes later.
Previous disruptions
Friday’s outage was not an isolated incident. X has experienced multiple high-profile service interruptions over the past two years. In November, tens of thousands of users reported widespread errors, including “Internal server error / Error code 500” messages. Cloudflare-related error messages were also reported.
In March 2025, the platform endured several brief outages spanning roughly 45 minutes, with more than 21,000 reports in the U.S. and 10,800 in the U.K., according to Downdetector. Earlier disruptions included an outage in August 2024 and impairments to key platform features in July 2023.
Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025
Tesla Sweden uses Megapack battery to bypass unions’ Supercharger blockade
