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.
Investor's Corner
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Elon Musk says Starship Flight 15 will try to catch the ship itself, a first.
Elon Musk says SpaceX’s next Starship flight will try something nobody has done before, by catching the ship itself. Speaking to roughly 2,000 people at the X Takeover event at Giga Texas on Saturday, Musk said Flight 15 is about four to six weeks away and “probably launches a little bit before Thanksgiving, is my guess.”
That is a slip from earlier reporting, which had pointed to a launch as early as October 19. Musk explained why the date keeps moving. “We’re making a bunch of improvements to the rocket between every flight,” he said, adding that there are often hundreds, sometimes thousands, of small changes. This time the list is short, “but some of them take a fair bit of work and we’ve got to go inside the tank to make some of these changes.”
“We’re going to try to catch the ship, which is a super big deal,” Musk said. “If we do so, that’ll be the first time that there’s been full recovery of an orbital class rocket.” SpaceX has already caught the Super Heavy booster with the tower’s mechanical arms, and has talked about catching the ship since late 2025, but the upper stage has never been caught.
Musk also laid out what comes after. “The next big milestone would be to refly both the booster and the ship,” he said, describing a Flight 16 where “all parts of an orbital rocket are reflown.”
The reason SpaceX wants this comes down to cost and cadence. Every Starship ship so far has ended its flight in the ocean, and SpaceX expects most of those water landings to end in fireballs. A ship that returns to Starbase intact can be inspected and flown again. SpaceX’s IPO filing, says Starship V3 is designed to deliver 100 metric tons to orbit in a fully reusable configuration, that SpaceX aims to cut the cost to reach orbit by 99% or more versus the historical average, and that tower catches should allow “multiple launches per day.”
The payoff goes beyond cheaper launches. The next generation Starlink V3 satellites are too large for Falcon 9 and can only fly on Starship, which can carry up to 60 per flight. Flight 14 on September 28 deployed the first 26 of them after Starship reached orbit despite an early engine shutdown, as Teslarati reported. Musk blamed engine computer software, and said the heat shield “was extremely robust,” which he claimed in August had solved Starship’s biggest challenge.
NASA’s Moon plans depend on the same capability. NASA’s inspector general has described a lander mission that needs a propellant depot in low Earth orbit and more than 10 tanker flights, with SpaceX targeting one tanker launch every six days. That schedule only works if ships and boosters come back fast and fly again. Also, ship to ship propellant transfer has not been attempted yet.
One interesting hurdle yet to be explored is bringing the ship back to the launch site, with reentry over land, which will undoubtedly come with a lot of aviation safety reviews.
Lifestyle
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla engineer confirms Cybercab update letting riders pull up rear and repeater cameras on demand.
Tesla is working on a Cybercab update that would let passengers pull up the vehicle’s rear and side cameras on demand, and the request came straight from a rider.
The exchange played out on X late Friday. Cybercab rider Dan Burkland shared photos of the two-seater’s cabin screen after an evening ride, praised the UI team’s work, and left one request: let riders open the rear and repeater cameras whenever they want, “especially for peace of mind.” Tesla UI software engineer Evan (@CarCoder) answered with two words: “In development.”
The Tesla UI team absolutely crushed it with the infotainment software. Nicely done @CarCoder!
One feature request: Allow folks to pull up the rear & repeater cameras on demand. This would be great especially for peace of mind. https://t.co/mNAOSLx6pE
— Dan Burkland (@DBurkland) October 10, 2026
The idea fits a pattern Teslarati has tracked since public rides began. Days after paid Cybercab service opened in Austin, Tesla sent riders a survey that asked them to rate the touchscreen, the app and the cabin, and to pick the features they wanted most. We reported on that survey in September, and a camera view is the kind of small software change Tesla can push quickly if riders keep asking.
It also speaks to something unique about the vehicle. With no steering wheel, no pedals and no driver, passengers have no mirror to check and no way to see behind them. The hardware is clearly built for camera awareness, from the repeater cameras to the rear camera. Letting a passenger look through those same cameras would give a nervous first time rider a way to confirm what is around the car.
The timing matters because the fleet is growing fast. Tesla’s Robotaxi account said on Saturday that more than 300 Cybercabs are now serving Austin, an eightfold increase in 30 days, and Tesla AI chief Ashok Elluswamy named Dallas as the next city. More cars and more cities mean more people riding in a driverless vehicle for the first time, which is exactly when small trust features carry weight.
For now, the feature is confirmed only as in development. If Tesla follows its usual pattern with Cybercab software, riders could see it appear in a point release without any announcement, and Teslarati will watch for it.
News
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
Tesla confirms its first official Cybercab fleet number as Austin scales fast and Dallas looms.
Tesla says more than 300 Cybercabs are now serving Austin, the first time the company has put an official number on its active Cybercab fleet. The figure came from the Robotaxi account on X on Saturday, which wrote that one month after launch the service had “scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days.”
Ashok Elluswamy, Tesla’s head of AI software, quoted the post with a line that carried the bigger news. “Two years since the 10/10 Cybercab WeRobot event, the cabs are everywhere in Austin now. Dallas soon,” he wrote. It is the first time Tesla has named the next city for public Cybercab rides.
One month after launch, we’ve scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days https://t.co/EagJy2JAsm
— Robotaxi (@robotaxi) October 10, 2026
Tesla opened Cybercab rides to the public in Austin on September 4, as Teslarati reported, a day after an invite only launch event. The ramp since then has been steep. Our September 28 report had the fleet at well over 100 units after availability jumped from 58 to 125 in a single week. On Thursday, Tesla added 150 Cybercabs to the Texas automated vehicle registry, lifting its registered count to 319 from 169. The first seven appeared on the registry on August 31.
RobotaxiTracker, a community site that counts vehicles from sightings and state records, listed 275 vehicles in unsupervised service in Austin on Saturday, 105 of them Cybercabs, which is well below Tesla’s figure. Tracker counts can lag official numbers, though Sawyer Merritt noted that Cybercab wait times in Austin stayed short on Saturday evening even with more than 2,000 fans in town for X Takeover.
Regulators are watching the rollout. NHTSA opened an audit query into Tesla’s certification that the Cybercab meets federal safety standards, and sworn answers are due October 30. Tesla reports third quarter earnings on October 21, which gives the company a natural venue to define its fleet numbers and put a date on Dallas.
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
The Pentagon taps Elon Musk to design the battlefield of the future
Tesla Roadster’s new patent preps white-knuckle speeds, keeping it grounded
