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.
Tesla rolled out Full Self-Driving version 14.2 yesterday to members of the Early Access Program (EAP). Expectations were high, and Tesla surely delivered.
With the rollout of Tesla FSD v14.2, there were major benchmarks for improvement from the v14.1 suite, which spanned across seven improvements. Our final experience with v14.1 was with v14.1.7, and to be honest, things were good, but it felt like there were a handful of regressions from previous iterations.
While there were improvements in brake stabbing and hesitation, we did experience a few small interventions related to navigation and just overall performance. It was nothing major; there were no critical takeovers that required any major publicity, as they were more or less subjective things that I was not particularly comfortable with. Other drivers might have been more relaxed.
With v14.2 hitting our cars yesterday, there were a handful of things we truly noticed in terms of improvement, most notably the lack of brake stabbing and hesitation, a major complaint with v14.1.x.
However, in a 62-minute drive that was fully recorded, there were a lot of positives, and only one true complaint, which was something we haven’t had issues with in the past.
The Good
Lack of Brake Stabbing and Hesitation
Perhaps the most notable and publicized issue with v14.1.x was the presence of brake stabbing and hesitation. Arriving at intersections was particularly nerve-racking on the previous version simply because of this. At four-way stops, the car would not be assertive enough to take its turn, especially when other vehicles at the same intersection would inch forward or start to move.
This was a major problem.
However, there were no instances of this yesterday on our lengthy drive. It was much more assertive when arriving at these types of scenarios, but was also more patient when FSD knew it was not the car’s turn to proceed.
Can report on v14.2 today there were ZERO instances of break stabbing or hesitation at intersections today
It was a significant improvement from v14.1.x
— TESLARATI (@Teslarati) November 21, 2025
This improvement was the most noticeable throughout the drive, along with fixes in overall smoothness.
Speed Profiles Seem to Be More Reasonable
There were a handful of FSD v14 users who felt as if the loss of a Max Speed setting was a negative. However, these complaints will, in our opinion, begin to subside, especially as things have seemed to be refined quite nicely with v14.2.
Freeway driving is where this is especially noticeable. If it’s traveling too slow, just switch to a faster profile. If it’s too fast, switch to a slower profile. However, the speeds seem to be much more defined with each Speed Profile, which is something that I really find to be a huge advantage. Previously, you could tell the difference in speeds, but not in driving styles. At times, Standard felt a lot like Hurry. Now, you can clearly tell the difference between the two.
It seems as if Tesla made a goal that drivers should be able to tell which Speed Profile is active if it was not shown on the screen. With v14.1.x, this was not necessarily something that could be done. With v14.2, if someone tested me on which Speed Profile was being used, I’m fairly certain I could pick each one.
Better Overall Operation
I felt, at times, especially with v14.1.7, there were some jerky movements. Nothing that was super alarming, but there were times when things just felt a little more finicky than others.
v14.2 feels much smoother overall, with really great decision-making, lane changes that feel second nature, and a great speed of travel. It was a very comfortable ride.
The Bad
Parking
It feels as if there was a slight regression in parking quality, as both times v14.2 pulled into parking spots, I would have felt compelled to adjust manually if I were staying at my destinations. For the sake of testing, at my first destination, I arrived, allowed the car to park, and then left. At the tail-end of testing, I walked inside the store that FSD v14.2 drove me to, so I had to adjust the parking manually.
This was pretty disappointing. Apart from parking at Superchargers, which is always flawless, parking performance is something that needs some attention. The release notes for v14.2. state that parking spot selection and parking quality will improve with future versions.
Any issues with parking on your end? 14.1.7 didn’t have this trouble with parking pic.twitter.com/JPLRO2obUj
— TESLARATI (@Teslarati) November 21, 2025
However, this was truly my only complaint about v14.2.
You can check out our full 62-minute ride-along below:
Elon Musk
SpaceX issues statement on Starship V3 Booster 18 anomaly
The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas.
SpaceX has issued an initial statement about Starship Booster 18’s anomaly early Friday. The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas.
SpaceX’s initial comment
As per SpaceX in a post on its official account on social media platform X, Booster 18 was undergoing gas system pressure tests when the anomaly happened. Despite the nature of the incident, the company emphasized that no propellant was loaded, no engines were installed, and personnel were kept at a safe distance from the booster, resulting in zero injuries.
“Booster 18 suffered an anomaly during gas system pressure testing that we were conducting in advance of structural proof testing. No propellant was on the vehicle, and engines were not yet installed. The teams need time to investigate before we are confident of the cause. No one was injured as we maintain a safe distance for personnel during this type of testing. The site remains clear and we are working plans to safely reenter the site,” SpaceX wrote in its post on X.
Incident and aftermath
Livestream footage from LabPadre showed Booster 18’s lower half crumpling around the liquid oxygen tank area at approximately 4:04 a.m. CT. Subsequent images posted by on-site observers revealed extensive deformation across the booster’s lower structure. Needless to say, spaceflight observers have noted that Booster 18 would likely be a complete loss due to its anomaly.
Booster 18 had rolled out only a day earlier and was one of the first vehicles in the Starship V3 program. The V3 series incorporates structural reinforcements and reliability upgrades intended to prepare Starship for rapid-reuse testing and eventual tower-catch operations. Elon Musk has been optimistic about Starship V3, previously noting on X that the spacecraft might be able to complete initial missions to Mars.
Investor's Corner
Tesla analyst maintains $500 PT, says FSD drives better than humans now
The team also met with Tesla leaders for more than an hour to discuss autonomy, chip development, and upcoming deployment plans.
Tesla (NASDAQ:TSLA) received fresh support from Piper Sandler this week after analysts toured the Fremont Factory and tested the company’s latest Full Self-Driving software. The firm reaffirmed its $500 price target, stating that FSD V14 delivered a notably smooth robotaxi demonstration and may already perform at levels comparable to, if not better than, average human drivers.
The team also met with Tesla leaders for more than an hour to discuss autonomy, chip development, and upcoming deployment plans.
Analysts highlight autonomy progress
During more than 75 minutes of focused discussions, analysts reportedly focused on FSD v14’s updates. Piper Sandler’s team pointed to meaningful strides in perception, object handling, and overall ride smoothness during the robotaxi demo.
The visit also included discussions on updates to Tesla’s in-house chip initiatives, its Optimus program, and the growth of the company’s battery storage business. Analysts noted that Tesla continues refining cost structures and capital expenditure expectations, which are key elements in future margin recovery, as noted in a Yahoo Finance report.
Analyst Alexander Potter noted that “we think FSD is a truly impressive product that is (probably) already better at driving than the average American.” This conclusion was strengthened by what he described as a “flawless robotaxi ride to the hotel.”
Street targets diverge on TSLA
While Piper Sandler stands by its $500 target, it is not the highest estimate on the Street. Wedbush, for one, has a $600 per share price target for TSLA stock.
Other institutions have also weighed in on TSLA stock as of late. HSBC reiterated a Reduce rating with a $131 target, citing a gap between earnings fundamentals and the company’s market value. By contrast, TD Cowen maintained a Buy rating and a $509 target, pointing to strong autonomous driving demonstrations in Austin and the pace of software-driven improvements.
Stifel analysts also lifted their price target for Tesla to $508 per share over the company’s ongoing robotaxi and FSD programs.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
SpaceX issues statement on Starship V3 Booster 18 anomaly
