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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.
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Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla’s Robotaxi app now shows ETAs, wait times and availability for Cybercab and Model Y.
Tesla has rolled out a new vehicle selection screen in its Robotaxi app, and it puts the numbers riders care about most in front of them before they book.
Version 26.11.0 of the app shows the estimated arrival time, the expected wait and current availability for each vehicle option on a single screen, according to a video shared by @gheeunit on X on November 7. Riders deciding between a Cybercab and a Model Y Robotaxi can now compare those figures side by side instead of picking a car first and learning how long it will take afterward.
Tesla first gave riders that choice on September 3, the day paid Cybercab rides began in Austin. The original version of the screen listed the Cybercab, which seats two, next to the Model Y, which seats four. A later build, 26.8.2, added a seating capacity indicator so groups knew which car would fit them. What it did not show was whether choosing the Cybercab meant standing on the curb a few extra minutes.
Newest version of @robotaxi app has a new vehicle selector UI for choosing between Cybercab and Model Y and shows you the fare for both simultaneously! https://t.co/7qoDQ0vACX — mantequilla 🧈 (@gheeunit) November 7, 2026
That question matters more now than it did two months ago. Tesla had 45 Cybercabs on the Texas DMV roster when rides started. By late October the state listed 573, alongside 631 Model Ys, and community trackers logged a record 1,576 Cybercab sightings across Austin on Halloween alone. With two large fleets sharing one service area, the closest car and the quickest pickup are not always the same vehicle.
Inline availability also changes what happens when demand spikes. If no Cybercab is free nearby, the rider sees that on the selection screen rather than after trying to book one.
For now the comparison is mostly an Austin feature. Riders in Dallas, Houston, Fort Worth and the Florida markets are still matched with Model Y vehicles, though Tesla said on its third quarter earnings call that Cybercab rides would launch in Dallas this month.
The update follows a steady run of smaller changes to the rider experience. Late last month Tesla brought a quiet mode that blacks out the cabin screen to Model Y Robotaxis after first testing it in the Cybercab, and it has stretched Austin service to run from 6 a.m. to 2 a.m.
The Cybercab side of that selection screen is about to get much busier. Elon Musk said this week that Tesla will wind down Cybertruck production at Gigafactory Texas around the middle of 2027 to make room for more Cybercab output, and Tesla has said it is aiming to get Cybercabs to customers by the end of this year.
Tesla has not published official release notes for version 26.11.0.
Tesla is ending Cybertruck production sometime in mid-2027, according to CEO Elon Musk.
Musk made the announcement on X last night, which came as a shock to many. He said that the Cybertruck will end production “to make room for increased Cybercab production” at Gigafactory Texas.
It is a huge blow to the fans of Tesla who have come to love the Cybertruck and identify with it as a symbol of their fandom. It has been the best-selling electric pickup, but it has had an underwhelming sales performance in terms of what was expected. This is mostly due to Tesla not meeting the prices it planned to offer the Cybertruck, as its unveiling and actual release were four years apart.
Tesla will be winding down production of the Cybertruck at Gigafactory Texas around the middle of next year to make room for increased Cybercab production
— Elon Musk (@elonmusk) November 6, 2026
Overall, the responses were mixed. Some fans understood the move toward Cybercab production, especially as Tesla is truly pushing the autonomous future through its Robotaxi platform. However, others did not understand it.
“Damn, how many Cybercabs do you guys need?” one response read. Another said it was “Sad but understandable.”Even analyst Gary Black had responded to the news, stating he hoped Tesla planned to replace it with a traditional pickup design.
It doesn’t seem like that will be the case.
Tesla is so hell-bent on delivering autonomy and eventually providing a driverless service that owning a car seems like an arbitrary idea, according to their thesis. Instead, Cybercabs will be available to pick you up and drop you off on demand, safely, without any human help.
As a result, Tesla has thinned its lineup considerably, and one can only ask where the vehicle lineup goes from here. Eventually, it seems like Cybercab could be the only vehicle that Tesla will sell.
Elon Musk
SpaceX’s next Starship flight set to make history on Friday the 13th
SpaceX is targeting Friday, November 13 for Starship Flight 15 and its first ship catch.
SpaceX is targeting Friday, November 13 for Starship Flight 15, the mission the company plans to use for its first attempt at catching the ship itself with the launch tower.
SpaceX Vice President of Launch Kiko Dontchev shared the date on stage at the UP.Summit on Thursday, according to Ars Technica’s Eric Berger, who was in attendance. It is the first launch target to come directly from a SpaceX executive. Until now, the public schedule had relied on FAA air traffic planning slides, which listed Flight 15 for no earlier than November 8 and later November 12. SpaceX has not posted an official mission page yet, and no launch time has been shared.
The date lands inside the window Elon Musk sketched out last month. Speaking at Giga Texas on October 10, Musk said the flight would “probably launch a little bit before Thanksgiving,” as Teslarati reported. On SpaceX’s third quarter earnings call ten days later, he confirmed that Flight 15 would try to catch both the Super Heavy booster and the ship, and put the odds of a successful ship catch at “more likely than not.” SpaceX also aired an animation of the maneuver during that webcast, showing the ship swinging vertical over Starbase before dropping into the tower’s chopsticks.
The hardware is ready. Booster 22 fired all 33 of its Raptor engines for a full duration static fire at Pad 2 on October 25. Ship 42 followed with a single engine burn simulating a deorbit maneuver on October 26 and a 60 second firing of all six engines the next day, according to NASASpaceflight. Ship 42 had already rehearsed the catch in September, when the Pad 2 arms lifted it into position and crews connected the quick disconnect arm while the vehicle hung from the tower.
The remaining hurdle is regulatory. The FAA’s Starship page does not yet list a Flight 15 license. SpaceX President Gwynne Shotwell said in October that, after “significant constructive engagement with the FAA,” she expects the license to cover a return to the launch site and a tower catch for both stages. Bringing the ship home means a reentry path that heads toward land, rather than ending over open ocean as every Starship flight so far has.
SpaceX has caught Super Heavy three times, on Flights 5, 7 and 8, but the ship comes back from orbital velocity and has never been caught. Flight 14 on September 28 was the first Starship to reach orbit, deploying 26 Starlink V3 satellites before splashing down despite an early engine shutdown that Musk blamed on engine computer software.
Musk has called a successful ship catch “the first time that there’s been full recovery of an orbital class rocket,” and he has already named the step after it: a Flight 16 where both the booster and the ship fly again. NASASpaceflight reports that Ship 43, the next vehicle in line, is set for static fire testing in December.
Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla is ending Cybertruck production
