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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.
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Tesla CEO Elon Musk outlines expectations for Cybercab production
“…initial production is always very slow and follows an S-curve. The speed of production ramp is inversely proportionate to how many new parts and steps there are. For Cybercab and Optimus, almost everything is new, so the early production rate will be agonizingly slow, but eventually end up being insanely fast.”
Tesla CEO Elon Musk outlined expectations for Cybercab production as the vehicle is officially set to start rolling off manufacturing lines at the company’s Giga Texas factory in less than 100 days.
Cybercab is specifically designed and catered to Tesla’s self-driving platform and Robotaxi ride-hailing service. The company has been pushing hard to meet its self-set expectations for rolling out an effective self-driving suite, and with the Cybercab coming in under 100 days, it now needs to push for Unsupervised Self-Driving in the same time frame.
Tesla CEO Elon Musk confirms Robotaxi is set to go unsupervised
This is especially pertinent because the Cybercab is expected to be built without a steering wheel or pedals, and although some executives have said they would build the car with those things if it were necessary.
However, Musk has maintained that the Cybercab will not have either of those things: it will have two seats and a screen, and that’s it.
With production scheduled for less than 100 days, Musk broke down what people should expect from the initial manufacturing phases, being cautiously optimistic about what the early stages will likely entail:
“…initial production is always very slow and follows an S-curve. The speed of production ramp is inversely proportionate to how many new parts and steps there are. For Cybercab and Optimus, almost everything is new, so the early production rate will be agonizingly slow, but eventually end up being insanely fast.”
Musk knows better than most about the challenges of ramping up production of vehicles. With the Model 3, Musk routinely refers to it as “production hell.” The Cybertruck, because of its polarizing design and stainless steel exterior, also presented challenges to Tesla.
With the important caveat that initial production is always very slow and follows an S-curve.
The speed of the production ramp is inversely proportionate to how many new parts and steps there are.
For Cybercab and Optimus, almost everything is new, so the early production…
— Elon Musk (@elonmusk) January 20, 2026
The Cybercab definitely presents an easier production process for Tesla, and the company plans to build millions of units per year.
Musk said back in October 2024:
“We’re aiming for at least 2 million units a year of Cybercab. That will be in more than one factory, but I think it’s at least 2 million units a year, maybe 4 million ultimately.”
When April comes, we will find out exactly how things will move forward with Cybercab production.
Tesla has revealed an awesome Model 3 and Model Y incentive to help consumers make the jump to one of its affordable mass-market vehicles, but it’s ending soon.
Tesla is offering one free upgrade on eligible inventory of the Model 3 and Model Y until February 2.
This would help buyers receive the most expensive paid option on the vehicle at no additional cost, meaning white interior or a more premium paint option will be free of charge if you take delivery on or before February 2.
Tesla states on its website for the offer:
“Only for limited inventory while supplies last. Price displayed on inventory listings already deducts the cost of the free option.”
Tesla says its one free upgrade offer on eligible U.S. inventory for the Model 3 and Model Y ends February 2.
With this incentive, buyers receive the most expensive paid option on the vehicle at no additional cost (up to $2k in savings). pic.twitter.com/IhoiURrsDI
— Sawyer Merritt (@SawyerMerritt) January 21, 2026
This latest incentive is just another advantage Tesla has by selling its vehicles directly and not using some sort of dealership model that relies on approvals from higher-ups. It is important to note that these programs are offered to help stimulate demand and push vehicles into customers’ hands.
It is not the only incentive Tesla is currently offering, either. In fact, there is a much larger incentive program that Tesla is working on, and it has to do with Full Self-Driving transfers, which could result in even more sales for the company through Q1.
Tesla is ending its FSD Transfer program on March 31, as it plans to transition to a Subscription-only basis with the self-driving suite for anyone who has not already purchased it outright.
This could help drive some on-the-fence buyers to new vehicles, but it remains to be seen. Given the timing of the program’s demise, it appears Tesla is hoping to use it to add additional sales and bolster a strong Q1 2026.
Interior and exterior paint colors can add up to $2,000 if you choose the most premium Ultra Red body color, or an additional $1,000 for the Black and White interior option. The discount, while small, could help get someone their preferred design configuration, instead of settling for something that is not quite what they want.
Tesla Full Self-Driving is getting an outrageous insurance offer with insanely cheap rates that will slash the cost of coverage by 50 percent.
Lemonade, a digital insurance company, has launched its first-of-a-kind product known as Lemonade Autonomous Car Insurance, and it is starting with an exclusive offer to FSD. The new offer will cut rates for FSD-engaged driving by “approximately 50 percent,” highlighting the data that shows a significantly safer driving environment when the suite is activated and engaged.
The company also said it plans to introduce even cheaper rates as Tesla continues to release more advanced FSD versions through software updates. Tesla has been releasing new FSD versions every few weeks, highlighting vast improvements for those who have the latest AI4 chip.
The announcement comes just a few months afterLemonade Co-Founder and President Shai Wininger said that he wanted to insure FSD vehicles for “almost free.” He said that Tesla’s API complemented Lemonade’s AI-based platform because it provides “richer and more accurate driving behavior data than traditional UBI devices.”
Tesla Full Self-Driving gets an offer to be insured for ‘almost free’
In mid-December, Lemonade then offered Tesla owners in California, Oregon, and Arizona the opportunity to connect their vehicles directly to the company’s app, which would provide a direct connection and would require a separate telematics device, which is required with other insurance providers who offer rates based on driving behaviors.
This latest development between Lemonade and Tesla is something that Wininger believes will be different because of the advanced nature of FSD:
“Traditional insurers treat a Tesla like any other car, and AI like any other driver. But a car that sees 360 degrees, never gets drowsy, and reacts in milliseconds can’t be compared to a human.”
He went on to say that the existing pay-per-mile product has given the company something that no traditional insurer has been able to offer. This comes through Lemonade’s “unique tech stack designed to collect massive amounts of real driving data for precise, dynamic pricing.”
The reputation FSD has gathered over the past few years is really impressive. Wininger backed this with some more compliments:
“Teslas driven with FSD are involved in far fewer accidents. By connecting to the Tesla onboard computer, our models are able to ingest incredibly nuanced sensor data that lets us price our insurance with higher precision than ever before.”
The product will begin its official rollout in Arizona on January 26. Oregon will get it a month later.
Tesla CEO Elon Musk outlines expectations for Cybercab production
Tesla reveals awesome Model 3 and Model Y incentive, but it’s ending soon
