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.
For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.
Would you buy a Tesla phone ? pic.twitter.com/aaTwvvIJit
— Tesla Owners Silicon Valley (@teslaownersSV) October 6, 2023
Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.
It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.
Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.
The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.
Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.
The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.
SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.
There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.
The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.
Tesla revealed a major new Cybercab detail in a guide it released for First Responders, showing new territory in its beliefs and intentions for the ride-hailing-focused vehicle that entered production in April.
The First Responders Guide is released to give fire departments, paramedics, and other emergency personnel the proper guidance on what to do in the event of an accident, entrapment, or other situation that would require immediate attention.
On one of the pages of the First Responders Guide, Tesla revealed a stark detail about the Cybercab, which could help personnel enter the vehicle more easily in case of an emergency.
Tesla Cybercab has one important piece that AI4 cars might need for FSD
It shows Tesla has no intention of releasing any Cybercab units that were initially proposed for ride-hailing services for the general public with any manual controls, meaning a steering wheel or pedals:
“A Cybercab equipped with steering wheel, brake pedal, and an acceleration pedal is typically an engineering or test vehicle, and operates at SAE Level 2 autonomy. Cybercab is not typically equipped with a steering wheel or acceleration and brake pedals.”
New official Cybercab documentation from Tesla:
“A Cybercab equipped with steering wheel, brake pedal, and an acceleration pedal is typically an engineering or test vehicle, and operates at SAE Level 2 autonomy. Cybercab is not typically equipped with a steering wheel or… https://t.co/P6ut1mZyzr pic.twitter.com/yq6skl9s2J
— Sawyer Merritt (@SawyerMerritt) June 27, 2026
This is a major development for those who continue to believe Tesla planned to release the Cybercab with any sort of manual controls so that passengers could take over if needed. However, when Tesla started manufacturing production versions of the Cybercab in Giga Texas earlier this year, they were spotted without a steering wheel or pedals.
It essentially confirms the company has no intentions of bringing manual controls to the car’s production versions. Some have argued that the likelihood of Tesla having something
There still are some Cybercab units out there with a steering wheel and pedals, and as Tesla said, these cars are engineering or test vehicles, which have Safety Monitors on board to help the car out of a precarious situation or emergency.
Tesla released the Full Self-Driving v14 ‘Lite’ suite to owners of Hardware 3 or AI3 vehicles today, adding several new features to the vehicles that were once believed to be capable of unsupervised self-driving.
Now, Tesla has released this modified suite to older Tesla vehicles, adding plenty of new features and capabilities.
Here are the full release notes for the suite:
- Distilled the intelligence from HW4 V14 into HW3. This allows HW3 to directly learn how to handle scenarios using HW4 V14 as a guide. This process unlocks the improvements that have been made to HW4 including Reinforcement Learning (RL) and offline models for HW3.
- Improved both proactive and reactive responsiveness across a wide variety of categories including navigation handling, merges and forks, pedestrian interactions, traffic lights, and vehicle cut-in scenarios.
- Improved general comfort in nominal scenarios through fewer false slowdowns, smoother steering and more consistent lane centering.
- Introduced parking, unparking, and reversing capabilities.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, or at the Curbside.
- Speed Profiles are now available at all times, to further customize driving style preference.
These improvements, according to Tesla’s Head of AI, Ashok Elluswamy, help distill the driving behavior from AI4’s v14 series into both the camera and compute configurations of AI3.
Tesla Full Self-Driving v14 ‘Lite’ for older cars finally gets released
He added:
“It includes destination options and speed profiles on city roads, but more importantly significantly improved safety. We hope you’ll enjoy it, once the build ships wide.”
FSD v14 Lite is now rolling out to AI3 early-access customers. Based on the feedback, will rollout to more customers over the next few weeks.
This build distills the driving behavior from AI4’s v14 series into both the camera and compute config of AI3. It includes destination…
— Ashok Elluswamy (@aelluswamy) June 29, 2026
Tesla will continue to roll out the v14 Lite suite more widely in the coming weeks, the company said.
Tesla Phone? Not quite, but close: analyst
Tesla reveals huge Cybercab detail in new guide for First Responders
