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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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Elon Musk

How to use Grok Bot to block spam calls and texts

Musk told users to ask Grok Bot to scrub their phone numbers from spam lists.

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Elon Musk has a new use case for Grok Bot, and it is the spam call. On Thursday he replied to an X user named Arash with a short instruction: “Ask your @Grok @Bot to remove your phone number from spam call & text lists!” Arash had said he got tired of the calls, had an AI bot find his number on listing sites and file removal requests, and packaged the process as a free skill for others.

The skill is called Spam-Call Scrubber, which is described to find a phone number on people search sites and data brokers, submits the opt outs, completes the confirmation emails those sites send back, and rechecks on a schedule the user picks. Using it requires the Grok Bot app. The pitch is time saved, since most broker opt outs sit behind separate forms on separate sites.



Musk said Grok Bot now gives each bot its own email address, and that it can detect scam emails. On Thursday he also said SpaceX would make users whole if the bot botches a purchase or leaks a card, then told users to shop away from Amazon after the retailer blocked the agent, as Teslarati reported. The terms of service we reviewed at the time put responsibility for what an agent does on the user.

For Tesla owners, Grok Bot is not just a phone app. Tesla brought Grok Bot into its vehicles on September 22, and we argued earlier this week that the Cybercab’s real advantage may be the errands it runs during a ride. Every Cybercab and the rest of the Model Y Robotaxi fleet has it enabled. The more routine tasks like this one become, the more a rider has reason to hand over something personal in the back seat.

The new Spam-Call Scrubber skill can be downloaded for free and works on sites that honor removal requests, while noting that listings can reappear, and illegal robocallers do not check any registry. Whether Spam-Call Scrubber cuts anyone’s call volume is something the first wave of users will find out, and Musk’s endorsement guarantees that wave is coming.

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Investor's Corner

Tesla’s flying Roadster just revealed something bigger than the car

Analysts say the Roadster demo puts a Tesla and SpaceX merger back on the table.

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Tesla’s new Roadster, upside down and trailing cold gas thruster smoke, flips over a lineup of Tesla vehicles at the Roadster unveiling near Waco, Texas on October 15, 2026. (Image: Tesla)
Tesla’s new Roadster, upside down and trailing cold gas thruster smoke, flips over a lineup of Tesla vehicles at the Roadster unveiling near Waco, Texas on October 15, 2026. (Image: Tesla)

The Roadster unveiling near Waco ended Thursday night, and by Friday morning much of the investor reaction had less to do with the car than with who owns the rocket technology inside it.

Wedbush analyst Dan Ives said the event “puts the Tesla/SpaceX relationship on the table in a tangible way,” pointing to the propulsion, pressure vessel and control hardware sitting on a Tesla product. Gene Munster of Deepwater Asset Management called the demo “a ridiculous display of engineering” with “no commercial value” beyond embarrassing traditional automakers, though he said it showed Musk wants the two companies together.

The more specific forecast came a day earlier from Barclays. Analyst Dan Levy told clients a deal could be announced before Tesla’s annual meeting, which must happen by December 6, and that an announcement in late October or early November could make shareholder approval harder. Barclays expects SpaceX to be the buyer in an all stock deal, with Tesla holders receiving SpaceX shares at a premium, based on market values of roughly $2.1 trillion for SpaceX and $1.5 trillion for Tesla. If nothing lands around the meeting, the bank still sees an announcement within 6 to 12 months.

The Roadster demo just added more weight to merger speculations. Tesla’s demo used cold gas thrusters and pressure tanks of the kind SpaceX uses on Falcon 9, and Musk described the car as a collaboration between Tesla and SpaceX engineers, as we mentioned in our breakdown of the three Roadster configurations.


Musk has not publicly addressed a deal since the event, as far as we have seen. His most direct answer remains the one he gave at the All In Summit, when he said that with so much collaboration, “who can imagine what action one might take” without ruling anything out. Ives has held to a 2027 timeline since his March note, and Musk pushed back on the China piece of the speculation when ARK floated a year end announcement in August.

The next test is Tesla’s third quarter earnings call on October 21. However, we recall in July that Musk told analysts, “we can’t talk about combining companies and that kind of thing on an earnings call,” so a clear answer wouldn’t be expected.

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How Tesla’s Roadster fan system and thrusters are built to dominate the corners

Tesla’s Roadster uses fans, active wings and cold gas thrusters to create grip at any speed.

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The Roadster’s rear wing, one of the aerodynamic elements Tesla pairs with a fan-based downforce system. (Image: Tesla)
The Roadster’s rear wing, one of the aerodynamic elements Tesla pairs with a fan-based downforce system. (Image: Tesla)

Tesla’s new Roadster is best known for flipping through the air in Texas, but the technology that matters most for a race track is the stuff that keeps it on the ground. Tesla’s Roadster page describes a multi-mode fan and ground sealing system that acts as a downforce generator, pulling air out from beneath the car. Tesla says it provides enough suction to hold the vehicle upside down, even when stationary.

That is the key difference from the wings and diffusers on a normal supercar. Conventional aero only makes downforce when the car is moving, and it grows with speed, so a car has the least grip in the slow corners and under hard braking. A fan system makes downforce at any speed. Tesla’s patent, which we covered last year, describes fans and deployable skirts that create sealed or partially sealed regions under the car, with the fans extracting air to lower the pressure and increase grip and stability.


Tesla pairs that with active wings, a next generation steer by wire system and a Track Mode that lowers the car and changes the suspension, with high downforce and low drag settings for the circuit. To keep weight down, Tesla points to magnesium, titanium and carbon fiber, manual controls and a fixed seat position, which it says lets the car respond to driver inputs almost instantly.

Tesla Roadster: Three configs, one can fly, 0-60 in 0.8 seconds

The cold gas thrusters are the other half. On the Thrust version they sit at the rear and Tesla says they take the car from 0 to 60 mph in under 0.9 seconds, while the Rocket version adds perimeter thrusters for forward, upward and lateral rotational movement. Tesla says the all electric actuators make micro adjustments within a fraction of a second.

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Musk has been talking about records for years. In June 2019 he said, “We’re going to do things with the new Roadster that are kind of unfair to other cars.” That September, when a follower asked whether the Roadster would beat the Nürburgring production car record, he replied with one word, “Absolutely,” as we reported at the time. In February 2024 he said Tesla had “radically increased the design goals” for the car and that its sub one second 0 to 60 time would be “the least interesting part.”

There are caveats. Tesla has not published a lap time or a verified cornering figure, so the record talk is still a promise rather than a result. Tesla also says the car is not approved for public road use, and the thruster features are limited to the Rocket trim, which is invite only. Fan cars have also been banned or withdrawn before, and getting a sealed underbody to work on a rough public road is a harder problem than on a smooth track. The first real test will be an official lap at a circuit.

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