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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.
Electric vehicle maker Lucid Group has denied rumors of an imminent bankruptcy after a report from this morning sent the stock on a dramatic drop on Wall Street, seeing losses of more than 40 percent during trading hours.
Lucid’s Director of Communications, Nick Twork, responded to the report from Eletric-Vehicles.com, which stated the company’s restructuring advisor, AlixPartners, was asked to review two decisions: taking Lucid shares private or filing for Chapter 11 bankruptcy protection.
The report also claims AlixPartners told the Lucid board to “concentrate on Gravity production while improving its quality, and to temporarily hold back the Lucid Air, the sedan that has defined the company since its launch.”
Twork said:
$LCID The rumors are completely false. The company has sufficient liquidity to carry its operations well into next year, as recently published in its last quarterly filings, and it has not formed any special Board committee to explore the scenarios reported today. Our focus is…
— Nick Twork (@ntwork) July 14, 2026
Shares rebounded after the response to the report, halving its losses as the trading day neared 3 p.m. Eastern.
Lucid has struggled to get its sales off the ground and into more respectable numbers, but the company is in its early years, when things are hard to begin with. It is also backed by several notable investors, including the Saudi Public Investment Fund (PIF), which has nearly limitless money and likely would not ditch an investment of this size so soon.
Lucid shares were down just 14 percent at the time of publication, a far cry from the 55 percent its losses topped out at during the day.
A Tesla owner who purchased a Model S Signature Edition, one of the final 250 units of the all-electric flagship vehicle that the company discontinued earlier this year, is attempting to sell the car despite a no-resale clause that prohibits reselling for the first year.
The car is being sold by J&S Autohaus in Ewing, New Jersey, and is priced at $260,490, well above the $159,420 that Tesla sold it for earlier this year.
🚨 The first Tesla Model S Signature Edition is up for sale for $260,490
Tesla placed a no-resale clause on the Model S and X Signature, so it will be interesting to see if the company takes any action. https://t.co/N9rKGHnbD6 pic.twitter.com/6FZhDL1KNR
— TESLARATI (@Teslarati) July 14, 2026
To those who do not know, the Model S Signature was a highly exclusive, limited-run farewell variant of the Model S Plaid that was produced this year to mark the end of production of both the Model S and Model X, Tesla’s two flagship vehicles.
Limited to just 250 units with invite-only sales, it serves as a collector’s item celebrating the legacy of the Model S, which helped pioneer Tesla’s electric vehicle success since its 2012 launch.
It bundles top-tier performance with bespoke cosmetic and luxury upgrades, plus Tesla’s Luxe Package. Here’s what the Model S Signature has over the typical Model S Plaid:
- Exclusive Exterior – Unique Garnet Red Paint, matching door handles, gold Tesla “T” badges upfront, gold Plaid and Signature badging at the rear.
- Premium Interior – White Alcantara upholstery with gold piping/accents, gold Plaid seat badges, Signature-marked door sills, individually numbered dashboard plaque, gold puddle lights, special interior lighting sequence, and a custom Signature key fob.
- Performance Upgrades – Carbon-ceramic brakes with gold calipers
- Bundled Luxe Package – Full Self-Driving (Supervised), four years of Premium Connectivity, free lifetime Supercharging
- Performance Metrics – ~1,020 horsepower, sub-2-second 0-60 MPH, ~390-mile range
Tesla quickly introduced a No Resale Agreement for the Signature Editions of the Model S and Model X, which would penalize the seller for “the amount of $50,000 or the value received as consideration for the sale or transfer, whichever is greater.”
The company continues:
“If you sell or otherwise transfer the ownership of your Model S or Model X, the remainder of the Recommended Maintenance, Wheel and Tire Protection Plan, and Windshield Protection Plan will transfer automatically to the buyer. The Full Self-Driving (Supervised), Free Supercharging and Premium Connectivity will not transfer with the vehicle and will terminate once the ownership of the Model S or Model X is transferred.”
Tesla will likely come after the seller, especially as it has been about two months since Tesla launched deliveries.
Tesla rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.
Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.
Tesla Full Self-Driving v14.3.5 Performance
The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.
Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.
We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.
FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:
🚨 Tesla Full Self-Driving v14.3.5 takes a wide turn as flagger crews set up signage for the day https://t.co/3v0PL9qhlI pic.twitter.com/i4CKqxE16c
— TESLARATI (@Teslarati) July 13, 2026
Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:
🚨 Tesla Full Self-Driving v14.3.5 backs up for an oncoming tractor trailer taking a wide turn https://t.co/0WuAqNMpRR pic.twitter.com/s6yZGVm5Te
— TESLARATI (@Teslarati) July 13, 2026
X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:
“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”
Check it out here:
Rapidfire epic moments on FSD V14.3.5
1) FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.
2) Insane speed to vehicle cues. As FSD approaches… pic.twitter.com/bSnySSlFHR
— Mike P (@mikepat711) July 13, 2026
It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.
Terrible Parking
Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:
Horrible first impression v14.3.5 on my 2025 Tesla Model 3 LR RWD Premium 😭
3 terrible parking jobs in 23 min including parking on a ramp in a business park & parking perpendicular out in the road on street only parking situation.
Wish I had a better drive but I still believe… pic.twitter.com/TtyhRHAFG7
— David Moss (@DavidMoss) July 13, 2026
New Features
Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:
🚨 Here’s the new Camera Preview feature on FSD v14.3.5 pic.twitter.com/OodfZgDppy
— TESLARATI (@Teslarati) July 13, 2026
Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.
Lucid denies rumors of bankruptcy after over 40% stock drop
Tesla owner attempts resale of Model S Signature Edition for over $260k
