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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.
Elon Musk
SpaceX’s newest logo confirms everything about what it’s become
SpaceX officially absorbed xAI under the SpaceXAI brand, completing the largest private merger in history.
SpaceX made its corporate transformation official in May 2026 when Elon Musk posted on X that xAI would cease to exist as a standalone company. “xAI will be dissolved as a separate company, so it will just be SpaceXAI, the AI products from SpaceX,” he wrote.
A new SpaceXAI logo was announced today, visually embedding the xAI letters inside the SpaceX identity, which can be seen as a deliberate design choice that signals the merger is not a partnership but a full absorption and XAi a core function of the same company. The same way Starlink is not a separate brand but a SpaceX product. The announcement closed the loop on a process that began February 2, 2026, when SpaceX acquired xAI in the largest private merger in history, valued at $1.25 trillion. SpaceX at $1 trillion and xAI at $250 billion.
We are now @SpaceXAI. pic.twitter.com/ema66xDWC9
— SpaceXAI (@SpaceXAI) July 6, 2026
The reason SpaceX bought xAI was stated plainly by Musk at the time of the deal: to build orbital data centers. SpaceX had simultaneously filed with the FCC to launch up to one million satellites designed to function as AI compute nodes in low Earth orbit, escaping what Musk described as the energy constraints limiting AI development on Earth.
xAI provided the AI software stack, with Grok, the X platform, and the Colossus supercomputer infrastructure in Memphis with over 220,000 NVIDIA GPUs, while SpaceX provided the rockets, Starlink, and the capital base to fund it. The two companies needed each other. xAI was burning $2.5 billion in losses on $250 million in revenue. SpaceX was generating an estimated $8 billion in profit on $15 billion in revenue and needed an AI narrative to command the valuation it was targeting for its IPO.
What SpaceX has done, regardless of how the orbital AI vision ultimately plays out, is walk into a public market as something no company has been before: a rocket manufacturer, satellite internet provider, AI software company, social media platform, and supercomputer operator under one ticker. Whether that combination is worth $2 trillion depends entirely on which of those businesses you believe in most.
Tesla brought its innovative Cybercab robotaxi to the National Federation of the Blind (NFB) Annual Convention in Austin, Texas, on July 3 at the JW Marriott Austin.
The hands-on demonstration highlighted the vehicle’s thoughtful design for blind and visually impaired users, underscoring Tesla’s commitment to inclusive autonomous mobility. Attendees, many using white canes or accompanied by service dogs, experienced the steering-wheel-free Cybercab firsthand.
Cybercab at the National Federation of the Blind’s Annual Convention in Austin for a hands-on experience of its accessibility features for blind or visually impaired customers⁰⁰For example:⁰– Braille lettering on physical controls
– Space for service animals & assistive… pic.twitter.com/8wrJcDHkw7— Tesla Robotaxi (@robotaxi) July 6, 2026
The showcase emphasized practical features tailored to the needs of the blind community. Braille lettering appears on physical controls, including door releases and emergency buttons, allowing users to navigate interfaces independently through touch. Generous interior space accommodates service animals and assistive devices such as canes, guide dogs, or mobility aids without compromising comfort.
Wheelchair-height seating facilitates easier transfers for users with additional mobility challenges. Photos from the event captured blind attendees approaching the vehicle confidently, service dogs relaxing inside, and hands exploring Braille-equipped handles.
Tesla Robotaxi’s official account detailed these elements, noting the Cybercab’s focus on accessibility, especially noting the Braille lettering and additional space for service animals.
How Tesla Will Transform Mobility for the Blind
Autonomous vehicles like the Cybercab promise revolutionary independence for the roughly 2.2 million visually impaired Americans. Traditional barriers—reliance on sighted drivers, costly paratransit, or limited public transit—often restrict spontaneous travel. Tesla Full Self-Driving aims to eliminate the need for a human operator, enabling on-demand, door-to-door rides via simple app hailing with voice guidance.
Users gain freedom to work, socialize, shop, or attend events anytime without scheduling hassles or safety concerns. This reduces isolation, boosts employment opportunities, and enhances quality of life, turning mobility from a dependency into true personal autonomy.
The NFB demonstration not only gathered valuable feedback but also generated excitement about a future where technology levels the playing field. By prioritizing inclusive design, Tesla advances a vision of transportation that serves everyone, potentially reshaping daily life for blind individuals and setting a standard for the autonomous industry.
As Cybercab deployment scales, these accessibility innovations could mark a significant step toward equitable mobility.
Investor's Corner
Tesla challenges startups to score a gig inside its most advanced European factory
Tesla is challenging startups to bring their best battery tech directly to Gigafactory Berlin.
Tesla has issued an open challenge to startups across Europe, inviting them to bring their best battery technology directly to the floor of Gigafactory Berlin. The program, called the JUNI x Tesla Battery Cell Giga Challenge, opened applications this month with a deadline of July 24, 2026, and is targeting startups with solutions that can make battery cell manufacturing faster, cheaper, safer, and more scalable at an industrial level.
The timing of the challenge is directly tied to Tesla’s most aggressive European battery investment yet. On May 12, 2026, Giga Berlin plant manager André Thierig announced a $250 million investment to scale the factory’s annual 4680 cell production capacity from 8 GWh to 18 GWh, more than doubling the previous target set just months earlier in December 2025. Thierig confirmed the expansion on X, saying the investment “will enable 18 GWh of annual 4680 cell production and create more than 1,500 new jobs.” Combined with a previously announced battery investment at the Grunheide site now approaches $1.2 billion.
Today, we announced a $ 250m investment for our Giga Berlin Cell factory. This will enable 18GWh of annual 4680 cell production and create more than 1500 new jobs. Good news during challenging times for the German industry. pic.twitter.com/ou4SWMfWh9
— André Thierig (@AndrThie) May 12, 2026
The challenge is looking specifically for startups with proven solutions across five categories: materials, equipment, operations, automation, and artificial intelligence. Applications are screened directly by Tesla’s cell manufacturing team in Grunheide, and the strongest submissions move through technical discussions, a pitch day in front of Tesla stakeholders, and potentially a paid pilot project with the cell team. Tesla is not looking for ideas at concept stage. The program requires applicants to demonstrate working prototypes, test data, or prior pilots before being considered.
The historical context matters here. Elon Musk first announced plans for what he called the world’s largest battery cell production facility alongside the Giga Berlin car factory back in 2020, targeting up to 250 GWh of annual capacity. Those plans were shelved in 2022 when Tesla shifted its battery investment focus to the United States to take advantage of Inflation Reduction Act incentives. The revival of cell production at Giga Berlin, now backed by over $1 billion in committed capital, represents a return to an ambition that was set aside for three years. As Teslarati has reported, the 4680 format is central to Tesla’s long-term cost reduction strategy across vehicles, energy storage, including the Tesla Semi and Cybercab.
By opening the challenge to outside startups, Tesla is acknowledging that reaching 18 GWh at Grunheide will require technology it does not currently have in-house, and it is willing to pay for the right solutions. For a startup in the battery supply chain, a paid pilot with Tesla’s European cell team is as close to a direct commercial path as the industry offers.
SpaceX’s newest logo confirms everything about what it’s become
Tesla flexes how it will help the blind with Cybercab
