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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 claps back at France’s Tesla Full Self-Driving approval delay

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Credit: Tesla

Elon Musk clapped back at France’s decision to withhold the approval for Tesla’s Full Self-Driving (FSD) Supervised system, projecting a clear and blunt message to French Transport Minister Phillippe Tabarot, after he publicly rejected the technology in its current form.

Tabarot outlines several concerns with Tesla Full Self-Driving in a detailed video statement, where he said, “The safety trade-offs are not yet sufficient to authorize it as it currently stands,” he said. He emphasized that FSD is not a true self-driving system and that the driver remains fully responsible.

Key issues Tabarot also brought up included allowing speeding when surrounding traffic exceeds limits and what he believes are insufficient guarantees of driver attention during complex urban maneuvers such as lane changes, intersections, and roundabouts.

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While acknowledging technological progress and France’s support for autonomous innovation, Tabarot stressed that deployment must prioritize road safety. He noted ongoing technical discussions with Tesla, the Netherlands, and other European partners, with further ecosystem meetings planned for the fall.

Musk’s rebuke highlights the human cost of regulatory caution. Tesla’s latest safety reports provide compelling data supporting accelerated adoption. In the most recent 12-month period, vehicles using FSD (Supervised) recorded one major collision per approximately 5.1 million miles driven, dramatically better than the U.S. national average of one crash per 698,000 miles.

Even Tesla vehicles driven manually with active safety features outperform the average by a wide margin. These figures come from billions of real-world miles of telemetry, showing FSD vehicles involved in far fewer incidents than both manual Teslas and the broader U.S. fleet.

Critics argue Tesla’s comparisons require careful scrutiny regarding reporting thresholds and fleet demographics, yet the data consistently positions FSD as a potential lifesaver. With road fatalities remaining a leading cause of death worldwide, Musk contends that proven safer technology should not face prolonged bureaucratic hurdles.

France’s measured approach reflects the broader European regulatory caution, which many, especially Musk, have been critical of in the past. However, as autonomous systems from Tesla and competitors like Waymo demonstrate superior safety in independent studies, pressure is mounting for harmonized approvals.

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Musk’s warning carries the belief that every month of delay may equate to avoidable tragedies on European roads.

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Investor's Corner

Google’s massive stake in SpaceX will shock you

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Credit: SpaceX

In a striking revelation that underscores the lucrative crossover between Big Tech and space exploration, Alphabet Inc., Google’s parent company, disclosed a massive $94.1 billion equity stake in SpaceX following the rocket company’s blockbuster initial public offering earlier this year.

The disclosure came in Alphabet’s quarterly filing, marking the first time the long-held private investment has been publicly valued at market prices. Google was an early backer, investing alongside Fidelity in 2015 with roughly $500-900 million at a time when SpaceX was valued around $12 billion.

That bet has delivered extraordinary returns, roughly a hundredfold, transforming a strategic play on satellite internet and launch capabilities into one of Alphabet’s largest assets.

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Of the total holding, approximately $80 billion remains subject to short-term post-IPO lockup restrictions, preventing near-term sales. An additional $14.1 billion faces longer-term restrictions, extending into the third quarter of 2027. This structure limits immediate liquidity but protects against market volatility as SpaceX transitions into public trading.

The SpaceX position contributed significantly to gains in Alphabet’s broader investment portfolio, which also includes a major stake in AI leader Anthropic. Combined, these holdings helped drive nearly $100 billion in investment gains during the second quarter, providing a substantial boost to net income amid ongoing AI spending pressures.

Elon Musk sends first warning to SpaceX short sellers

Analysts view the disclosure as validation of Alphabet’s venture strategy beyond its core search and cloud businesses. The investment aligns with deeper ties, including reported multi-billion-dollar deals for AI computing capacity on SpaceX infrastructure. As SpaceX advances Starship flights, Starlink expansion, and ambitious Mars goals under Elon Musk, Google’s stake positions it to benefit from the commercialization of space.

For Alphabet, the windfall highlights how patient, forward-looking bets in transformative sectors can yield outsized rewards. While lockups temper short-term impact, the holding cements SpaceX as a cornerstone of Alphabet’s diversified portfolio in an era where aerospace, AI, and connectivity increasingly intersect. Investors will watch closely as restrictions lift and SpaceX’s public performance unfolds.

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Tesla’s switch-up on selling Full Self-Driving has paid off big time

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In early 2026, Tesla made a bold strategic pivot: it largely eliminated the option to purchase Full Self-Driving (FSD) software outright and shifted to a subscription-only model. The change, effective around mid-February, ended the one-time fee that had previously ranged as high as $15,000 and later dropped to $8,000. Instead, customers would access FSD (Supervised) for $99 per month in the U.S.

At the time, skeptics questioned whether locking customers into recurring payments would hurt adoption or alienate buyers who preferred ownership of the feature. Tesla bet that a lower barrier to entry, seamless integration at purchase, and the ability to cancel at any time would drive higher uptake.

The results from Q2 2026 speak for themselves: the decision has been a resounding success, delivering the largest quarterly growth in FSD subscriptions in the company’s history.

According to Tesla’s Q2 shareholder update, active FSD subscriptions reached 1.48 million globally by the end of June 2026. That represents a 56 percent increase year-over-year and a 15.6 percent jump from the prior quarter. Tesla added roughly 200,000 new subscriptions in the period alone—the biggest single-quarter gain on record.

North America led the charge, with more than 55 percent of new vehicle deliveries including an FSD subscription at the time of purchase, a record attach rate for the region.

Tesla explicitly noted that “more customers [are] opting for subscription at the time of vehicle purchase,” crediting the model shift and prominent placement of the option in the ordering process. Subscriptions now contribute meaningfully to ancillary revenue, helping offset pressure elsewhere in the business.

The financial upside is substantial: At $99 per month, 1.48 million active subscriptions generate approximately $146.5 million in monthly recurring revenue. Over a full year, that equates to roughly $1.76 billion in annualized recurring revenue (ARR) from FSD subscriptions alone, assuming steady retention and no major pricing changes.

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These figures represent pure, high-margin software revenue. Unlike vehicle sales, which carry production costs, warranty obligations, and supply-chain risks, FSD subscriptions flow largely to the bottom line once the software is developed and deployed over-the-air.

Tesla does not break out exact FSD subscription revenue in its filings (it sits within “Services and Other”), but the category grew 50 percent year-over-year in Q2, with executives highlighting subscriptions as a key driver.

The subscription model offers several structural advantages. It lowers the upfront cost of a new Tesla, potentially broadening the buyer pool and supporting vehicle demand, especially important amid fluctuating EV market conditions. It creates a predictable revenue stream that compounds as the fleet grows and more owners try (and stick with) the software.

Legacy one-time purchasers still exist, but new growth is overwhelmingly subscription-based following the February cutoff.

Early data also suggests improving retention and satisfaction, as well. Tesla has rolled out iterative FSD updates, including v14 features, and expanded availability to additional markets. Recent regulatory approvals in parts of Europe have further boosted interest, with owners in newly enabled countries eager to activate the software they had been waiting for.

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FSD is still supervised; regulatory hurdles for true unsupervised autonomy persist in many regions, including the United States, and competition in advanced driver-assistance systems is intensifying. Yet the Q2 numbers validate Tesla’s bet: by removing the large upfront commitment and making FSD accessible via subscription, the company has accelerated adoption faster than many anticipated.

What began as a controversial switch-up has become a clear win. With nearly 1.5 million subscribers, record attach rates, and nearly $1.8 billion in potential annual recurring revenue already in view, Tesla’s FSD business is transitioning from a promised future to a tangible, fast-growing profit engine.

If the momentum continues, and especially if unsupervised capabilities unlock robotaxi opportunities, the subscription flywheel could become one of the most valuable assets in Tesla’s portfolio.

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