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Stanford studies human impact when self-driving car returns control to driver
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.
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.
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.
News
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.
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.
Our new 125 kW Basecharger is designed for longer dwell times and overnight charging of Semis. It’s the “home charging” for heavy-duty fleets.
It features a fully integrated design that eliminates the need for a separate AC-to-DC cabinet, simplifying installation. The 6 meter… https://t.co/ovy1C4PsRW pic.twitter.com/vBUCNMzs57
— Tesla Charging (@TeslaCharging) May 1, 2026
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.
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.
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.
News
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.
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.
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:
Thank you Tesla! The new intervention screen is much better! @Tesla_AI pic.twitter.com/1lea9G27N1
— Dirty Tesla (@DirtyTesLa) May 1, 2026
There will likely be one additional revision to the Interventions Menu, as we have coined it here at Teslarati.
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.
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.
Lifestyle
California hits Tesla Cybercab and Robotaxi driverless cars with new law
California just gave police power to ticket driverless cars, including Tesla’s Cybercab fleet.
California DMV formally adopted new rules on April 29, 2026 that allow law enforcement to issue “notices of noncompliance”, or in other words ticket autonomous vehicle companies when their cars commit moving violations. The rules take effect July 1, 2026 and officially closes a regulatory gap that previously let driverless cars operate on public roads with nearly no traffic enforcement consequences.
Until now, state traffic laws only applied to human “drivers,” which meant that when no person was behind the wheel, police had no mechanism to issue a ticket. Officers were limited to citing driverless vehicles for parking violations only. A well-known example came in September 2025, when a San Bruno officer watched a Waymo robotaxi execute an illegal U-turn and could do nothing but notify the company.
Under the new framework, when an officer observes a violation, the autonomous vehicle company is effectively treated as the driver. Companies must report each incident to the DMV within 72 hours, or 24 hours if a collision is involved. Repeated violations can result in fleet size restrictions, operational suspensions, or full permit revocation. Local officials also gained new authority to geofence driverless vehicles out of active emergency zones within two minutes and require a live emergency response line answered within 30 seconds.
Tesla Cybercab ramps Robotaxi public street testing as vehicle enters mass production queue
California’s new enforcement rules arrive at a pivotal moment for Tesla. The company is ramping Cybercab production at Giga Texas toward hundreds of units per week, targeting at least 2 million units annually at full capacity, while simultaneously pushing to expand its Robotaxi service to dozens of U.S. cities by end of 2026. Unsupervised FSD for consumer vehicles is currently targeted for Q4 2026, and when it arrives, Tesla’s fleet may not have a human to absorb legal accountability, under the July 1 rules.
Tesla has confirmed plans to expand its Robotaxi service to seven new cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, with the service already running without safety drivers in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year.
Tesla Semi gets new product launch as mass manufacturing hits Plaid Mode
Tesla revises new Intervention Reporting system with Full Self-Driving
