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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 will increase its Full Self-Driving subscription price, meaning it will eventually be more than the current $99 per month price tag it has right now.
Already stating that the ability to purchase the suite outright will be removed, Tesla CEO Elon Musk said earlier this week that the Full Self-Driving subscription price would increase when its capabilities improve:
“I should also mention that the $99/month for supervised FSD will rise as FSD’s capabilities improve. The massive value jump is when you can be on your phone or sleeping for the entire ride (unsupervised FSD).”
This was an expected change, especially as Tesla has been hinting for some time that it is approaching a feature-complete version of Full Self-Driving that will no longer require driver supervision. However, with the increase, some are concerned that they may be priced out.
$99 per month is already a tough ask for some. While Full Self-Driving is definitely worth it just due to the capabilities, not every driver is ready to add potentially 50 percent to their car payment each month to have it.
While Tesla has not revealed any target price for FSD, it does seem that it will go up to at least $150.
I should also mention that the $99/month for supervised FSD will rise as FSD’s capabilities improve.
The massive value jump is when you can be on your phone or sleeping for the entire ride (unsupervised FSD). https://t.co/YDKhXN3aaG
— Elon Musk (@elonmusk) January 23, 2026
Additionally, the ability to purchase the suite outright is also being eliminated on February 14, which gives owners another reason to be slightly concerned about whether they will be able to afford to continue paying for Full Self-Driving in any capacity.
Some owners have requested a tiered program, which would allow people to pay for the capabilities they want at a discounted price.
Unsupervised FSD would be the most expensive, and although the company started removing Autopilot from some vehicles, it seems a Supervised FSD suite would still attract people to pay between $49 and $99 per month, as it is very useful.
Tesla will likely release pricing for the Unsupervised suite when it is available, but price increases could still come to the Supervised version as things improve.
This is not the first time Musk has hinted that the price would change with capability improvements, either. He’s been saying it for some time. In 2020, he even said the value of FSD would “probably be somewhere in excess of $100,000.”
The FSD price will continue to rise as the software gets closer to full self-driving capability with regulatory approval. It that point, the value of FSD is probably somewhere in excess of $100,000.
— Elon Musk (@elonmusk) May 18, 2020
Tesla has chosen to axe the ability to purchase Full Self-Driving outright from a select group of cars just days after CEO Elon Musk announced the company had plans to eliminate that option in February.
The company is making a clear-cut stand that it will fully transition away from the ability to purchase the Full Self-Driving suite outright, a move that has brought differing opinions throughout the Tesla community.
Earlier this week, the company also announced that it will no longer allow buyers to purchase Full Self-Driving outright when ordering a pre-owned vehicle from inventory. Instead, that will be available for $99 per month, the same price that it costs for everyone else.
The ability to buy the suite for $8,000 for a one-time fee at the time of order has been removed:
NEWS: Tesla no longer allows buyers to purchase FSD outright in the U.S. when ordering a pre-owned vehicle directly from inventory. Tesla now gives you the option to either subscribe for $99/month, or purchase FSD outright after taking delivery (available until February 14th). pic.twitter.com/1xZ0BVG4JB
— Sawyer Merritt (@SawyerMerritt) January 23, 2026
This is a major move because it is the first time Tesla is eliminating the ability to purchase FSD outright for one flat fee to any of its vehicles, at least at the time of purchase.
It is trying to phase out the outright purchase option as much as it can, preparing people for the subscription-based service it will exclusively offer starting on February 14.
In less than a month, it won’t be available on any vehicle, which has truly driven some serious conversation from Tesla owners throughout the community.
There’s a conflict, because many believe that they will now lose the ability to buy FSD and not pay for it monthly, which is an attractive offer. However, others believe, despite paying $8,000 for FSD, that they will have to pay more money on top of that cost to get the unsupervised suite.
Additionally, CEO Elon Musk said that the FSD suite’s subscription price would increase over time as capabilities increase, which is understandable, but is also quite a conflict for those who spent thousands to have what was once promised to them, and now they may have to pay even more money.
News
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
These camera washers are crucial for keeping the operation going, as they are the sole way Teslas operate autonomously. The cameras act as eyes for the car to drive, recognize speed limit and traffic signs, and travel safely.
Tesla Robotaxi has a highly-requested hardware feature that is not available on typical Model Ys that people like you and me bring home after we buy them. The feature is something that many have been wanting for years, especially after the company adopted a vision-only approach to self-driving.
After Tesla launched driverless Robotaxi rides to the public earlier this week in Austin, people have been traveling to the Lone Star State in an effort to hopefully snag a ride from one of the few vehicles in the fleet that are now no longer required to have Safety Monitors present.
BREAKING: Tesla launches public Robotaxi rides in Austin with no Safety Monitor
Although only a few of those completely driverless rides are available, there have been some new things seen on these cars that are additions from regular Model Ys, including the presence of one new feature: camera washers.
With the Model Y, there has been a front camera washer, but the other exterior “eyes” have been void of any solution for this. For now, owners are required to clean them manually.
In Austin, Tesla is doing things differently. It is now utilizing camera washers on the side repeater and rear bumper cameras, which will keep the cameras clean and keep operation as smooth and as uninterrupted as possible:
🚨 Tesla looks to have installed Camera Washers on the side repeater cameras on Robotaxis in Austin
pic.twitter.com/xemRtDtlRR— TESLARATI (@Teslarati) January 23, 2026
Rear Camera Washer on Tesla Robotaxi pic.twitter.com/P9hgGStHmV
— TESLARATI (@Teslarati) January 24, 2026
These camera washers are crucial for keeping the operation going, as they are the sole way Teslas operate autonomously. The cameras act as eyes for the car to drive, recognize speed limit and traffic signs, and travel safely.
This is the first time we are seeing them, so it seems as if Safety Monitors might have been responsible for keeping the lenses clean and unobstructed previously.
However, as Tesla transitions to a fully autonomous self-driving suite and Robotaxi expands to more vehicles in the Robotaxi fleet, it needed to find a way to clean the cameras without any manual intervention, at least for a short period, until they can return for interior and exterior washing.
Tesla to increase Full Self-Driving subscription price: here’s when
Tesla starts removing outright Full Self-Driving purchase option at time of order
