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

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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.

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.

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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.

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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.

"I write about technology and the coming zero emissions revolution."

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Starlink is ‘biggest competitive advantage,’ but it’s temporary, United CEO says

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Credit: United Airlines

United Airlines CEO Scott Kirby said that SpaceX’s Starlink satellite internet is its leading competitive advantage in the U.S. airline industry. However, in recent comments, while he described the service as “the biggest competitive advantage” the carrier currently holds, he also acknowledged that the edge is temporary.

“…everybody eventually is going to have high-speed low earth orbit internet connectivity. It’s going to be a must-have. We are going to have a few years of being the only airline that has it at scale, and that’s our mission,” Kirby said. Until everyone has it, United aims to capitalize on its head start by converting trial users into long-term loyal customers.

United has moved faster than its rivals on Starlink installations. As of mid-to-late October 2026, the system was on roughly 43 percent of its fleet, with plans to reach 61 percent by year-end, 87 percent by June 2027, and full fleet coverage by the end of next year.

The airline already operates more Starlink-equipped flights than the rest of the U.S. industry combined. Los Angeles International Airport is scheduled to become United’s first 100 percent Starlink hub in the first half of 2027, and the carrier’s app will display the likelihood that any given flight has the service.

Kirby has pointed to early evidence that the offering influences booking decisions. Some passengers loyal to other airlines are already switching flights for Starlink connectivity, something the airline, along with American Airlines, has tried to leverage against competing airlines. Both companies used status-match programs, and some of those customers are pursuing company-specific credit cards, which signals an intent to stay.

Once onboard, these customers encounter the airline’s broader investments in aircraft, larger seat-back screens, oversized bins, connection tools, and a mobile app that Kirby says outperforms competitors. Wi-Fi satisfaction scores on Starlink-equipped planes have been reported to be nearly double those on aircraft with other systems.

Competitors are moving slowly to do the same. Southwest Airlines began installations in 2025 and expects to complete them soon. Delta is pursuing Amazon’s Leo system, while American expects to start Starlink work in early 2027 and has not yet detailed regional-fleet plans. This timeline gap gives United a multi-year window in which it remains the only major U.S. carrier offering Starlink at scale.

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Kirby has framed the strategy as pressing that advantage while simultaneously widening gaps in other technology areas so that customers who try United for the Wi-Fi remain for the overall experience.

The approach reflects a calculated bet that superior in-flight connectivity can accelerate share gains and support longer-term financial targets, including a 10 percent pre-tax margin goal.

High-speed internet is particularly valued by premium and business travelers who can work or stream reliably. As low-Earth-orbit service becomes ubiquitous, the temporary nature of the pure connectivity edge means United’s retention will depend on whether its other product and operational improvements keep pace.

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Tesla Cybercab’s unorthodox paint process explained

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Credit: Tesla

Tesla Cybercab skips the traditional paint shop entirely, marking an unorthodox process for coloring the fully autonomous vehicle. However, the decision was a smart one, as it slashed factory costs, floor space utilization, and complexity, since Tesla relied on specialized alloys and in-mold coloring.

Munro Live was given the opportunity to do a factory walkthrough with Tesla Vice President of Vehicle Engineering Lars Moravy, who explained and detailed how Cybercab production at Giga Texas eliminates one of the automotive manufacturing industry’s most expensive and space-hungry elements.

A conventional paint line can cost hundreds of millions of dollars and require a million man-hours to build. Moravy framed the choice around Tesla’s core rule: “Question the requirements: why do you need paint?”

The structural answer lies in material selection. The aluminum alloys used in Cybercab’s front and rear castings do not oxidize and lose strength over time, the way many common automotive aluminum alloys do. Only the side modules, built around hot-stamped boron-steel door rings, receive an anti-corrosion e-coat, or dip coat. Front and rear modules skip coating altogether.

Model Y and Model 3 bodies, by contrast, are fully coated and painted.

Exterior colors come from the plastics shop, which Tesla engineers described as “our paint shop” for the Cybercab. Body panels are produced via reaction injection molding, referred to as RIM. Color is then mixed into a polyurethane resin at the mix head immediately before injection, so the panel emerges already colored with a Class-A surface.

Robots trim overflow to control sink marks and flow lines. The process avoids conventional spray-paint defects like orange peel and paint bleed. Scratches can still be repaired with compatible coatings that behave “basically like paint.” Because color is integral rather than a surface layer, shallow scratches do not expose a contrasting undercoat.

The secret behind Tesla’s Cybercab Gold goes well beyond just the color

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Tesla has also explored related approaches, including in-mold lamination and painted films on stamped panels.

The manufacturing payoff is substantial because removing the paint shop, combined with the “unboxed” modular process that builds and tests front, rear, side, and center modules in parallel before a short final assembly, cuts factory floor space per vehicle by about 50 percent.

Final assembly itself uses only about 25 automated stations, far fewer than the typical Model Y line, and the overall line runs at about 78 percent automation, Moravy said. The approach also eliminates volatile organic compound emissions associated with traditional spray painting for these panels and shortens the coloring cycle from hours to minutes.

Cybercab’s paint strategy is clearly less about aesthetics than about systematically deleting capital-intensive, energy-heavy, and space-consuming steps once material science and process design make them unnecessary. It is a concrete example of Tesla applying first-principles questioning to one of the auto industry’s most entrenched factory requirements.

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Tesla has a Cybercab problem nobody saw coming

Tesla’s Cybercab line now builds robotaxis faster than Tesla can deploy them, Lars Moravy says.

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Tesla’s Cybercab line in Texas can now build the two seat robotaxi faster than the company can put it into service, according to Lars Moravy, Tesla’s Vice President of Vehicle Engineering. “We don’t run every day because the line can run so fast. It’s currently outpacing our deployments,” Moravy said in a new Cybercab deep dive from Munro Live. “So, it’s a bit of a race right now. Who’s going to go faster? Right now the manufacturing line’s ahead.”

Tesla’s official Robotaxi account shared a Cybercab analysis video on X on Monday, calling it a “Cybercab engineering deep dive.” Moravy’s comments go further than what he told analysts on the Q3 earnings call last week, when he said the Cybercab line’s listed capacity of more than 125,000 units a year undersells what it can actually run.

The tour shows where that speed comes from. Tesla’s unboxed process splits the Cybercab into front, rear, side and center modules that are built and tested on their own before they meet on a short final line. That final line has just 25 fully automated stations, which Tesla’s team estimated is a fifth to a tenth of what a Model Y needs. The full line is about 78% automated, the framing line is already at 100%, and the layout uses roughly 50% less floor space per vehicle. The stated goal is “100% automation in 10 second cycle time,” or one finished Cybercab every 10 seconds.

Tesla also deleted the paint shop. Only the side modules are coated, and the exterior panels get their color inside the molding machine. Engineers said the car is designed to run at least 500,000 miles, which matters for a vehicle that will spend most of its day carrying riders.

The battery got the same treatment. The Cybercab uses an 88S6P pack of 4680 cells in a steel enclosure, a first for Tesla, with each module potted separately so a single failed module can be swapped instead of the whole pack. Wireless battery management boards replace a wiring harness, and new contactors are fast enough to drop the pyro fuse entirely. Tesla’s battery director graded the pack an A minus, compared with a D for the Model Y structural pack and a B minus for Cybertruck. Up front, the drive unit runs an 11:1 gear ratio versus roughly 9:1 on most Teslas, since the Cybercab does not need a high top speed.

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The deployment side is now the bottleneck Moravy described. Tesla had more than 50 Cybercabs working the Formula 1 weekend in Austin, and Texas records show 463 Cybercabs registered. Tesla said on its earnings call that Cybercab service will launch in Dallas next month, and Moravy said the company is aiming to get Cybercabs to customers by the end of 2026. Every unit built so far has gone into Tesla’s own fleet since the line moved into volume production in April.

Munro Live also asked when it could get a Cybercab to tear down. Tesla’s answer: “Not yet.”

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