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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.

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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.

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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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Tesla Cybercab just rolled through Miami inside a glass box

Tesla paraded a Cybercab in a glass display at Miami’s F1 Grand Prix event this week.

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Tesla Cybercab at the Miami F1 Fan Fest 2026: Credit: TESLARATI

Tesla set up an “Autonomy Pop-Up” at Lummus Park in Miami Beach from April 29 through May 3, 2026, embedded within the official F1 Miami Grand Prix Fan Fest.  The centerpiece was a Cybertruck towing the Cybercab inside a glass display case marked “Future is Autonomous,” rolling through the beachfront crowd.

Miami is on Tesla’s confirmed list of cities for robotaxi expansion in the first half of 2026, making the promotion a strategic promotion that lays groundwork in a target market.

This was not Tesla’s first time using Miami as a showcase city. In December 2025, Tesla hosted “The Future of Autonomy Visualized” at its Miami Design District showroom, coinciding with Art Basel Miami Beach. That event featured the Cybercab prototype and Optimus robots interacting with attendees. The F1 pop-up this week marks Tesla’s return to Miami and follows a pattern Tesla has been running since early 2026. Just two weeks before Miami, Tesla stationed Optimus at the Tesla Boston Boylston Street showroom on April 19 and 20, directly on the final stretch of the Boston Marathon, letting tens of thousands of runners and spectators meet the robot for free, generating massive earned media at zero advertising cost.

Tesla is sending its humanoid Optimus robot to the Boston Marathon

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Tesla has confirmed plans to expand its robotaxi service to seven cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, building on the unsupervised service already running in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year. On the production side, Musk told shareholders that the Cybercab manufacturing process could eventually produce up to 5 million vehicles per year, targeting a cycle time of one unit every ten seconds. Scaling robotaxis to 10 million operational units over the next ten years is a key condition of his compensation package, alongside selling 20 million passenger vehicles.

As for the Cybercab’s price, Musk has said buyers will be able to purchase one for under $30,000, with an average operating cost around $0.20 per mile. Whether those numbers hold through full production remains to be seen.

Cybercab at F1 Fan Fest in Miami
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Tesla Semi gets new product launch as mass manufacturing hits Plaid Mode

While the 1.2 MW Megacharger handles quick 30-minute en-route boosts, the Basecharger serves as a reliable overnight solution for longer dwell times at warehouses, distribution centers, fleet yards, and even, potentially, homes.

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Credit: Tesla

The Tesla Semi is getting a new production launch as mass manufacturing on the all-electric truck is gearing up to hit Plaid Mode.

Tesla has introduced a game-changing addition to its commercial charging lineup with the new 125 kW Basecharger for Semi. Launched this week as part of the new “Semi Charging for Business” program, this compact unit is purpose-built for depot and overnight charging of Tesla Semi trucks.

While the 1.2 MW Megacharger handles quick 30-minute en-route boosts, the Basecharger serves as a reliable overnight solution for longer dwell times at warehouses, distribution centers, fleet yards, and even, potentially, homes.

Delivering up to 60 percent of the Semi’s range in roughly four hours, perfect for overnight top-ups during mandated driver rest periods or while trucks are loaded or unloaded. Its fully integrated design eliminates the need for bulky separate AC-to-DC cabinets.

Tesla engineers tucked one of the power modules from a V4 Supercharger Cabinet directly inside the sleek post, resulting in a compact footprint. It also features a six-meter cable for layout flexibility. This is one thing that must have been learned through the V4 Supercharger rollout.

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Installation and operating costs drop dramatically thanks to daisy-chaining. Up to three Basechargers can share a single 125 kVA breaker, slashing electrical infrastructure requirements. The unit outputs 150 amps continuous across an 180–1,000 VDC range, matching the Semi’s high-voltage architecture while supporting the MCS 3.2 standard.

Tesla Semi sends clear message to Diesel rivals with latest move

Priced from $40,000 for a minimum order of two units, the Basecharger is far more affordable than the $188,000 Megacharger setup for two posts. Deliveries begin in early 2027. Buyers also receive Tesla’s full network-level software, remote monitoring, maintenance, and a guaranteed 97 percent or higher uptime—critical for fleet reliability.

This launch arrives as Tesla accelerates high-volume Semi production at its Nevada factory, targeting 50,000 units annually. By pairing affordable depot charging with ultra-fast highway options, Tesla removes one of the biggest obstacles to electrifying Class 8 trucking: infrastructure cost and complexity.

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Fleet operators stand to gain lower electricity rates during off-peak hours, dramatically reduced maintenance compared to diesel, and quieter yards at night. The Basecharger isn’t just another charger—it’s the practical bridge that makes large-scale electric semi adoption economically viable.

With the Basecharger handling “home” duties and Megachargers powering the road, Tesla is delivering a complete ecosystem that could finally tip the scales toward zero-emission freight. For trucking companies ready to go electric, the future just got a whole lot more charger-friendly.

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Tesla revises new Intervention Reporting system with Full Self-Driving

It is the second revision to the program as Tesla is trying to make it easier to decipher driver and owner complaints, but also to make it easier to report issues within the suite for them.

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Credit: Tesla

Tesla has revised its new Intervention Reporting system within the Full Self-Driving suite that now categorizes reasons that drivers take over when the semi-autonomous driving functionality is active.

It is the second revision to the program as Tesla is trying to make it easier to decipher driver and owner complaints, but also to make it easier to report issues within the suite for them.

With the initial rollout of Full Self-Driving v14.3.2, Tesla included a new reporting menu that gave four options for an intervention: Preference, Comfort, Critical, and Other. A slightly revised version of Full Self-Driving with the same ID number then came out a few days later, changing the “Other” option to “Navigation” after numerous complaints from owners.

It appears Tesla has listened to those owners once again and has not only made it smaller and more compact, but also easier to report the issues than previously.

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The new menu is now embedded within the request for a Voice Memo from Tesla, and does not block the entire screen, as the second rollout of the menu was:

There will likely be one additional revision to the Interventions Menu, as we have coined it here at Teslarati.

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Unfortunately, at times, there are no reasons for an intervention at all, but the menu does not give an option to simply disregard the reporting and forces the driver to choose one of the options. We, as well as other notable Tesla influencers, indicated that there is not always a reason for an intervention.

For example, I choose to back into my parking spot in my neighborhood at least some of the time for the reason of charging. I usually hit “Preference” for this, but it sends a false positive to Tesla that there was a reason I took over that I was unhappy with.

Tesla begins probing owners on FSD’s navigation errors with small but mighty change

Instead, I’m simply performing a maneuver that is not yet available to us. When Tesla allows drivers to choose the orientation at which their car enters a parking spot, I and many others won’t have to deal with this menu.

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Others are still skeptical that it will help resolve any issues whatsoever and prefer to disregard the menu altogether. It does seem as if Tesla will issue another revision in the coming days to allow this to happen.

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