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Stanford studies human impact when self-driving car returns control to driver

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9 years ago

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Tesla Autopilot in 'Shadow Mode' will pit human vs computer

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.

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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.

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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.

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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.

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Tesla improves Dashcam playback with awesome addition

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3 hours ago

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June 2, 2026

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Image Credit: The Kilowatts/Twitter

Tesla has improved Dashcam playback with an awesome new addition, as the company has launched a web-based version that is potentially easier to navigate and operate.

The tool is available at dashcam.tesla.com and will be enabled as your vehicle receives the 2026.20 Software Version. Clips that are captured by your Tesla will be available on the Online Dashcam Clip Viewer once the files on your car’s storage drive are encrypted.

Not a Tesla App first noticed the new feature, and states that once your Tesla updates to 2026.20, the car will automatically protect the clips with an encryption key that is uniquely tied to your owner account.

The web-based viewer should be easier to operate for most. All you will do is head over to dashcam.tesla.com and log in using your account credentials.

Ensure your vehicle is updated to 2026.20 in order for the web-based viewer tool to fetch your vehicle’s saved dashcam clips.

Currently, only a small percentage of owners are updated to this, so it may be a couple of weeks until a majority of owners in the fleet are able to access this feature.

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Watching Dashcam clips on the Tesla smartphone app is quick and convenient, as they can also be easily downloaded and stored right on your smartphone.

However, the clips are sometimes tougher to navigate, and in order to get details like self-driving activation, speed, and turn signals, owners have to screen record the Tesla app and crop out the rest of the screen.

It could also be a massive storage saver as you’ll be able to download the Dashcam clips from the online viewer and save them to your laptop, desktop, a flash drive, or even an external hard drive. This will keep all your clips in one place.

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Tesla Full Self-Driving attempts 150-mile stress test: the good and the bad

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6 hours ago

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June 2, 2026

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Credit: TESLARATI

I recently took my Tesla Model Y running Full Self-Driving (Supervised) v14.3.3 over 150 miles on the Pennsylvania Turnpike in an effort to truly put the system under a stress test. There were a lot of good moments, and some bad, but overall, Full Self-Driving impressed me.

Last Thursday, I decided it was time to visit the Flight 93 National Memorial near Shanksville, PA. I go a few times a year, and it was a beautiful day. Others have taken some pretty lengthy drives using FSD, but I haven’t had the opportunity to really do something lengthy in quite a few months on an older version. I decided it was the perfect opportunity to try some things out.

I recorded the entire ride there on a GoPro, edited to highlight the crucial moments, and shared them on our social media accounts. If you want to watch them, I’ll share them throughout the piece, but I did not get to do a real breakdown of what I felt about its performance.

Overall Thoughts

I realize it is probably better to do a summation of its performance toward the end of the piece, but I feel like it is also reasonable to lead with this because I was overly impressed with how well it handled everything. The only moments where I felt a little bit of reason to touch the wheel, at least while traveling on the Turnpike and Rt. 30, were due to other drivers and their behaviors.

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I have taken many drives to the Memorial over the past several years, and although it’s not incredibly long, it is a tiring drive. It’s about five hours both ways, close to 300 miles, and I think most of the exhaustion comes from the toll of sitting in the car and then visiting something that is pretty heavy to take in.

This was the first time I’ve ever taken the ride and not felt like I needed to avoid my vehicle after I got home. In the past, I could not even think about driving after I finally arrived at my house, but this was simply different.

It was nice to have something else take the drive for me, while I still had the freedom to take over if I chose to. It made the entire trip more enjoyable.

Full Self-Driving Recognizes Lane-Ending Arrows on Road

After traveling in the fast lane for a little while, FSD noticed the arrows on the road indicating the lane was coming to an end ahead. The car was also in the process of making a pass on a slower vehicle in the middle lane, but aborted this maneuver and backed off to get behind the vehicle.

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I was really impressed by this because I thought that the car would absolutely try to make the pass, only to get in front of the other car, and then slow back down to 75 MPH:

Full Self-Driving Notices Veering Tractor Trailer, Adjusts Lane Positioning

My two rules of the road are never cruise in the fast lane and never drive next to a tractor-trailer. This clip is a perfect example as to why.

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FSD v14.3.3 recognized this tractor-trailer attempting to change lanes while we were still next to it. The car shifted its lane positioning to the shoulder slightly to make room for the merging semi, executed the pass safely, and on we went.

I will admit this one made me a little nervous, but more so because of the 18-wheeler, and not because of the Tesla:

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Full Self-Driving Follows the Rules of Tunnel Travel

Many people who are not familiar with Full Self-Driving and its capabilities are pretty limited in what they know about the really simple things it does well. Part of supervising FSD is being aware of things it might make mistakes with, and anticipating maneuvers it might want to make at the wrong time.

Entering the Blue Mountain Tunnel on the Turnpike, I was ready for FSD to attempt to get back into the right lane after making a pass on a tractor-trailer, but I was pleasantly surprised. Several signs outside the tunnel advise drivers to stay in the lane they’ve chosen while driving through the tunnel; this eliminates the possibility of an accident caused by lane changes, which would impede traffic on a crucial logistics route.

I was happy to see that Tesla Full Self-Driving v14.3.3 did not make this mistake:

Full Self-Driving Navigates Toll Plazas with Ease

I was interested to see how FSD would handle toll plazas, including the speed at which it would travel through them, and whether it would stop on the Turnpike at these booths, which have since been transitioned to a “Toll by Plate” system, which mails you a bill.

It was flawless:

Full Self-Driving Still Struggles with Parking from Time to Time

Since I took delivery in late August, I’ve never had a single instance of my Tesla struggling to park at a Supercharger. Other spots at the mall, market, or gym are another story.

This was the first time it did such a terrible job of backing into a spot. This required me to take over and manually park at another charger:

Full Self-Driving Gets Confused After Arriving at Its Destination

This was the first time I have ever experienced FSD getting confused and just circling the lot. The navigation continued to reroute to try to resolve the issue, but after four laps, I decided it was time to overtake the car’s controls and park manually:

This was a baffling behavior that I truly couldn’t explain. Other owners communicated that they have also experienced this issue.

Final Thoughts

I am so incredibly impressed by FSD that it has really made traveling stress-free. The two issues related to parking were not ideal, but to be fair, I usually take over when arriving at parking lots. However, this shortcoming is something Tesla has to make some serious progress with, because parking has truly stumped FSD at times.

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Solving that will be a major breakthrough for autonomy, but Tesla has struggled with it for some time.

All in all, FSD v14.3.3 is unbelievably accurate and handles many of the more stressful maneuvers with ease, one of them being avoiding merging traffic on highways, which was shown above.

Some things that would be great to see improvements on are parking, Speed Profiles, which are relatively tough to adjust (I stayed in Standard for the duration of this drive), and, of course, navigation.

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SpaceX’s amended S-1 is sparking a major Tesla merger conversation

A single line in SpaceX’s amended S-1 just sent Tesla stock down 5% in one day.

Published

19 hours ago

on

June 1, 2026

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A single line buried in SpaceX’s amended S-1 filing is doing more to move Tesla’s stock price than anything Tesla itself has announced in months. The clause, disclosed as SpaceX prepares for what could be the largest IPO in Wall Street history, states that the company “may issue a significant amount of equity in connection with future transactions.” While this may be seen as boilerplate language in S-1 filings, the historical ties between SpaceX and Tesla, and with Elon Musk reportedly discussing a possible merger with close colleagues, investors are interpreting it as something closer to a signal.

The concern among institutional investors like Gary Black, managing director of The Future Fund, pointed directly to the amended filing on X, saying it “strongly suggests more SPCX equity will be issued,” which could potentially be used to acquire Tesla. He estimated such a deal could be 28% dilutive to Tesla shareholders since SpaceX would likely command a significantly higher valuation multiple. Black added that institutional investors he knows hate the idea of a combination because they prefer pure plays over conglomerates, which he said “nearly always gravitate to the lowest common multiple.”

The Tesla and SpaceX merger everyone is talking about is quietly building

The bull case runs the math differently. Tesla influencer and retail shareholder advocate AleXandra Merz pushed back on what she called a widespread misunderstanding of how merger-of-equals deals actually work. Rather than simply splitting the difference between two market caps, a merger exchange ratio is negotiated based on relative fair market values, meaning the lower valued company typically sees its stock reprice upward toward the deal value.

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Under her model, SpaceX enters at a $2.5 trillion valuation and Tesla at $1.6 trillion, producing a combined entity worth $4.1 trillion split evenly between both shareholder groups. That implies Tesla’s side of the deal would be valued at $2.05 trillion, a gain of roughly $450 billion from its current market cap. She cited Dow-DuPont and CBS-Viacom as historical examples of how markets reprice both companies toward the announced exchange ratio after a deal is unveiled.


The SpaceX S-1 amendments also revealed just how much financial infrastructure already binds the two companies together. As Teslarati has reported, SpaceX purchased $697 million in Tesla Megapacks, $131 million in Cybertrucks, and the two companies have shared supply chain resources, and semiconductor fabrication plans since well before any merger conversation became public. A retail poll by Tesla influencer Sawyer Merritt is finding that 36% of respondents do not plan to buy SpaceX shares at IPO and 15.3% saying their decision depends on the valuation.


Whether the merger happens or not, the amended filing is seemingly moving markets and sharpened a debate that is no longer theoretical. SpaceX is weeks away from trading publicly, and Tesla shareholders are now watching every word of every filing for clues about what Musk plans to do next.

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