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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.

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“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.

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“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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Elon Musk

Elon Musk’s net worth is nearing $800 billion, and it’s no small part due to xAI

A newly confirmed $20 billion xAI funding round valued the business at $250 billion, adding an estimated $62 billion to Musk’s fortune.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

Elon Musk moved within reach of an unprecedented $800 billion net worth after private investors sharply increased the valuation of xAI Holdings, his artificial intelligence and social media company. 

A newly confirmed $20 billion funding round valued the business at $250 billion, adding an estimated $62 billion to Musk’s fortune and widening his lead as the world’s wealthiest individual.

xAI’s valuation jump

Forbes confirmed that xAI Holdings was valued at $250 billion following its $20 billion funding round. That’s more than double the $113 billion valuation Musk cited when he merged his AI startup xAI with social media platform X last year. Musk owned roughly 49% of the combined company, which Forbes estimated was worth about $122 billion after the deal closed.

xAI’s recent valuation increase pushed Musk’s total net worth to approximately $780 billion, as per Forbes’ Real-Time Billionaires List. The jump represented one of the single largest wealth gains ever recorded in a private funding round.

Interestingly enough, xAI’s funding round also boosted the AI startup’s other billionaire investors. Saudi investor Prince Alwaleed Bin Talal Alsaud held an estimated 1.6% stake in xAI worth about $4 billion, so the recent funding round boosted his net worth to $19.4 billion. Twitter co-founder Jack Dorsey and Oracle co-founder Larry Ellison each owned roughly 0.8% stakes that are now valued at about $2.1 billion, increasing their net worths to $6 billion and $241 billion, respectively.

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The backbone of Musk’s net worth

Despite xAI’s rapid rise, Musk’s net worth is still primarily anchored by SpaceX and Tesla. SpaceX represents Musk’s single most valuable asset, with his 42% stake in the private space company estimated at roughly $336 billion. 

Tesla ranks second among Musk’s holdings, as he owns about 12% of the EV maker’s common stock, which is worth approximately $307 billion.

Over the past year, Musk crossed a series of historic milestones, becoming the first person ever worth $500 billion, $600 billion, and $700 billion. He also widened his lead over the world’s second-richest individual, Larry Page, by more than $500 billion.

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Tesla Cybercab sighting confirms one highly requested feature

The feature will likely allow the Cybercab to continue operating even in conditions when its cameras could be covered with dust, mud, or road grime.

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Credit: @DennisCW_/X

A recent sighting of Tesla’s Cybercab prototype in Chicago appears to confirm a long-requested feature for the autonomous two-seater. 

The feature will likely allow the Cybercab to continue operating even in conditions when its cameras could be covered with dust, mud, or road grime.

The Cybercab’s camera washer

The Cybercab prototype in question was sighted in Chicago, and its image was shared widely on social media. While the autonomous two-seater itself was visibly dirty, its rear camera area stood out as noticeably cleaner than the rest of the car. Traces of water were also visible on the trunk. This suggested that the Cybercab is equipped with a rear camera washer.

As noted by Model Y owner and industry watcher Sawyer Merritt, a rear camera washer is a feature many Tesla owners have requested for years, particularly in snowy or wet regions where camera obstruction can affect visibility and the performance of systems like Full Self-Driving (FSD).

While only the rear camera washer was clearly visible, the sighting raises the possibility that Tesla may equip the Cybercab’s other external cameras with similar cleaning systems. Given the vehicle’s fully autonomous design, redundant visibility safeguards would be a logical inclusion.

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The Cybercab in Tesla’s autonomous world

The Cybercab is Tesla’s first purpose-built autonomous ride-hailing vehicle, and it is expected to enter production later this year. The vehicle was unveiled in October 2024 at the “We, Robot” event in Los Angeles, and it is expected to be a major growth driver for Tesla as it continues its transition toward an AI- and robotics-focused company. The Cybercab will not include a steering wheel or pedals and is intended to carry one or two passengers per trip, a decision Tesla says reflects real-world ride-hailing usage data.

The Cybercab is also expected to feature in-vehicle entertainment through its center touchscreen, wireless charging, and other rider-focused amenities. Musk has also hinted that the vehicle includes far more innovation than is immediately apparent, stating on X that “there is so much to this car that is not obvious on the surface.”

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Tesla seen as early winner as Canada reopens door to China-made EVs

Tesla had already prepared for Chinese exports to Canada in 2023 by equipping its Shanghai Gigafactory to produce a Canada-specific version of the Model Y.

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Credit: Tesla

Tesla seems poised to be an early beneficiary of Canada’s decision to reopen imports of Chinese-made electric vehicles, following the removal of a 100% tariff that halted shipments last year.

Thanks to Giga Shanghai’s capability to produce Canadian-spec vehicles, it might only be a matter of time before Tesla is able to export vehicles to Canada from China once more. 

Under the new U.S.–Canada trade agreement, Canada will allow up to 49,000 vehicles per year to be imported from China at a 6.1% tariff, with the quota potentially rising to 70,000 units within five years, according to Prime Minister Mark Carney. 

Half of the initial quota is reserved for vehicles priced under CAD 35,000, a threshold above current Tesla models, though the electric vehicle maker could still benefit from the rule change, as noted in a Reuters report.

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Tesla had already prepared for Chinese exports to Canada in 2023 by equipping its Shanghai Gigafactory to produce a Canada-specific version of the Model Y. That year, Tesla began shipping vehicles from Shanghai to Canada, contributing to a sharp 460% year-over-year increase in China-built vehicle imports through Vancouver. 

When Ottawa imposed a 100% tariff in 2024, however, Tesla halted those shipments and shifted Canadian supply to its U.S. and Berlin factories. With tariffs now reduced, Tesla could quickly resume China-to-Canada exports.

Beyond manufacturing flexibility, Tesla could also benefit from its established retail presence in Canada. The automaker operates 39 stores across Canada, while Chinese brands like BYD and Nio have yet to enter the Canadian market directly. Tesla’s relatively small lineup, which is comprised of four core models plus the Cybertruck, allows it to move faster on marketing and logistics than competitors with broader portfolios.

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