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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.
Lifestyle
NTSB findings on fatal Tesla crash tell a very different story
The NTSB confirmed the driver, not Tesla’s FSD, caused the fatal Texas house crash.
The National Transportation Safety Board released preliminary findings Wednesday confirming that a Tesla driver, not the vehicle’s software, caused a fatal crash in Katy, Texas in June. The driver, 44-year-old Michael Butler, had engaged Full Self-Driving Supervised mode on Rose Hollow Lane, a residential street with a 30 mph speed limit, before manually overriding the system by pressing the accelerator pedal all the way to 100%. Data recovered from the 2025 Tesla Model 3 showed the vehicle was traveling over 70 miles per hour when it struck a home and killed 76-year-old Martha Avila, who was inside. Weather was clear, the road was dry, and it was daylight.
Texas man charged in fatal Tesla crash where he blamed Autopilot
Butler told authorities he had passed out at the wheel. But security camera footage obtained by the NTSB told a different story, and showed the car accelerating through an intersection before leaving the road entirely. Police also found that Butler’s phone had Google searches including the terms “Tesla FSD not aggressive enough 2026” and “Tesla FSD too timid,” raising serious questions about how he was using the system before the crash. Butler has since been charged with manslaughter. The victim’s family has filed a lawsuit against both Butler and Tesla, alleging negligence.
The NTSB findings aligned directly with what Tesla VP of AI Software Ashok Elluswamy had already stated publicly on X in the weeks after the crash, writing that “the driver manually overrode self-driving by pressing the accelerator all the way to 100%.” The data confirmed his account.
Yup. In this case, the driver manually overrode self-driving by pressing the accelerator all the way to 100% of the accel pedal in this residential area. They reached a speed of 73 mph during the crash, and had the accelerator pressed even after the crash.
— Ashok Elluswamy (@aelluswamy) June 22, 2026
Lucid CEO Silvio Napoli responded to rumors of an imminent bankruptcy that was reportedly being mulled after a report stated the automaker was working with the firm AlixPartners to iron out its next steps.
The company felt a massive loss on Wall Street yesterday, as the report essentially pushed the stock down as much as 55 percent on Tuesday.
The report, published initially by Eletric-Vehicles.com, claimed Lucid was essentially in dire straits and was told by AlixPartners, a commonly used restructuring advisor, to either take shares private or file for Chapter 11 bankruptcy protection.
Lucid’s head of Communications, Nick Twork, immediately challenged the report and stated the company “has sufficient liquidity to carry its operations well into next year.”
Now, the company’s CEO is chiming in as well, stating that the report is “so far from the facts that they require a direct response.”
Napoli said:
“Lucid is not considering bankruptcy or a transaction to take the company private. Those reports are false. The Board did not explore either scenario. Period.
As disclosed in our most recent quarterly filing, Lucid has sufficient liquidity to fund its operations well into next year.
We work with outside advisors to improve operational performance and execution. They are not advising Lucid on a take-private transaction or bankruptcy, and any suggestion that they have recommended either course of action to management or the Board is false.
My priority is clear: turn this company around. That is where the leadership team and I are focused.
I look forward to providing a full update during our quarterly earnings call on August 4th.”
🚨 Lucid CEO Silvio Napoli calls rumors of financial issues “so far from the facts that they require a direct response.”
Read his full remarks here: https://t.co/t3Pg1NHvzy pic.twitter.com/LvHUPhO4Qf
— TESLARATI (@Teslarati) July 15, 2026
It seems pretty clear that Lucid is confident things will be okay, and, to be honest, they should not have much to worry about, especially considering the company has been backed by the Saudi Public Investment Fund (PIF) for years. It has solid financial backing, and its sales, while weak, are pretty much right on par with a company of this age.
Lucid also sent a Cease & Desist letter to the publication for their report.
Lucid shares have rebounded nicely and are up nearly 21 percent at the time of publication. As soon as the company dispelled the rumors of bankruptcy yesterday, the stock began to climb back toward more reasonable levels.
Tesla has once again demonstrated strong customer focus by swiftly addressing and fully refunding a bizarre Supercharger pricing glitch that affected drivers in Atlantic Canada.
The issue surfaced earlier this month when the Tesla app began displaying dramatically inflated per-minute charging rates at stations in Prince Edward Island and parts of New Brunswick.
One widely shared screenshot from a Charlottetown, PEI Supercharger showed rates reaching ridiculous levels: $6.00 per minute for the 180-250 kW tier, along with $3.57/min for 100-180 kW and $2.29/min for 60-100 kW.
Correct pricing will be going live at midnight tonight. All fees since July 2nd 2026 will be waived.
— Tesla Charging (@TeslaCharging) July 13, 2026
These figures were several times higher than normal Supercharger pricing in the region.
To put the error in perspective, charging at the highest incorrect rate would have been shockingly expensive.
At 250 kW, a common charging speed at Superchargers, a vehicle pulls roughly 4.17 kWh per minute. Under the glitch, a driver spending just 10 minutes at peak power would face a $60 bill. A typical 20- to 30-minute session to add meaningful range could have cost $120 to $180 or more, before any congestion fees.
Tesla gets another layer of gamification with Free Supercharging on the line
By comparison, standard Canadian Supercharger rates usually fall between $0.25 and $0.60 per kWh, making a similar session cost roughly $15–$40. The erroneous per-minute structure, combined with the inflated numbers, turned what should be a convenient stop into a potential financial shock.
The glitch appears to have started sometime around early July, and quickly drew attention on social media as owners questioned whether Tesla had implemented steep hidden increases. Some drivers even reported seeing $0 charges in their history, indicating broader billing confusion.
Tesla’s official Charging account on X stated that correct pricing would roll out at midnight on July 13, so the fix is already in effect. More importantly, the company announced it would waive all fees for every Supercharger session since July 2. This blanket waiver covers the entire affected period without requiring users to file individual claims, with automated refunds expected soon. The decision affects stations in PEI and nearby areas in New Brunswick and Nova Scotia.
It’s a classy move, and rather than issuing partial credits or forcing owners to submit support tickets, Tesla simply absorbed the cost of the system error and made drivers whole. In an industry where hidden fees and bill disputes are common, Tesla’s proactive, no-questions-asked approach reinforces owner trust and highlights the company’s commitment to service excellence.
The incident, while disruptive for a short time, ultimately showcases Tesla’s ability to own mistakes and prioritize customer satisfaction. Atlantic Canada Tesla owners can now charge with confidence again, knowing the company has their back when technology glitches occur.
In an era of complex EV billing, such transparency and generosity are refreshing and set a positive example for the industry.
NTSB findings on fatal Tesla crash tell a very different story
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