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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
Starlink restrictions are hitting Russian battlefield comms: report
The restrictions have reportedly disrupted Moscow’s drone coordination and frontline communications.
SpaceX’s decision to disable unauthorized Starlink terminals in Ukraine is now being felt on the battlefield, with Ukrainian commanders reporting that Russian troops have struggled to maintain assault operations without access to the satellite network.
The restrictions have reportedly disrupted Moscow’s drone coordination and frontline communications.
Lt. Denis Yaroslavsky, who commands a special reconnaissance unit, stated that Russian assault activity noticeably declined for several days after the shutdown. “For three to four days after the shutdown, they really reduced the assault operations,” Yaroslavsky said.
Russian units had allegedly obtained Starlink terminals through black market channels and mounted them on drones and weapons systems, despite service terms prohibiting offensive military use. Once those terminals were blocked, commanders on the Ukrainian side reported improved battlefield ratios, as noted in a New York Post report.
A Ukrainian unit commander stated that casualty imbalances widened after the cutoff. “On any given day, depending on your scale of analysis, my sector was already achieving 20:1 (casuality rate) before the shutdown, and we are an elite unit. Regular units have no problem going 5:1 or 8:1. With Starlink down, 13:1 (casualty rate) for a regular unit is easy,” the unit commander said.
The restrictions come as Russia faces heavy challenges across multiple fronts. A late January report from the Center for Strategic and International Studies estimated that more than 1.2 million Russian troops have been killed, wounded, or gone missing since February 2022.
The Washington-based Institute for the Study of War also noted that activity from Russia’s Rubikon drone unit declined after Feb. 1, suggesting communications constraints from Starlink’s restrictions may be limiting operations. “I’m sure the Russians have (alternative options), but it takes time to maximize their implementation and this (would take) at least four to six months,” Yaroslavsky noted.
Elon Musk
Tesla Korea hiring AI Chip Engineers amid push for high-volume AI chips
Tesla Korea stated that it is seeking “talented individuals to join in developing the world’s highest-level mass-produced AI chips.”
In a recent post on X, Tesla Korea announced that it is hiring AI Chip Design Engineers as part of a project aimed at developing what the company describes as the world’s highest-volume AI chips. CEO Elon Musk later amplified the initiative.
Tesla Korea stated that it is seeking “talented individuals to join in developing the world’s highest-level mass-produced AI chips.”
“This project aims to develop AI chip architecture that will achieve the highest production volume in the world in the future,” Tesla Korea wrote in its post on X.
As per Tesla Korea, those who wish to apply for the AI Chip Design Engineer post should email Ai_Chips@Tesla.com and include “the three most challenging technical problems you have solved.”
Elon Musk echoed the hiring push in a separate post. “If you’re in Korea and want to work on chip design, fabrication or AI software, join Tesla!” he wrote.
The recruitment effort in South Korea comes as Tesla accelerates development of its in-house AI chips, which power its Full Self-Driving (FSD) system, Optimus humanoid robot, and data center training infrastructure.
Tesla has been steadily expanding its silicon development teams globally. In recent months, the company has posted roles in Austin and Palo Alto for silicon module process engineers across lithography, etching, and other chip fabrication disciplines, as noted in a Benzinga report.
Tesla Korea’s hiring efforts align with the company’s long-term goal of designing and producing AI chips at massive scale. Musk has previously stated that Tesla’s future AI chips could become the highest-volume AI processors in the world.
The move also comes amid Tesla’s broader expansion into AI initiatives. The company recently committed about $2 billion into xAI as part of a Series E funding round, reinforcing its focus on artificial intelligence across vehicles, robotics, and compute infrastructure.
Elon Musk
SpaceX and xAI tapped by Pentagon for autonomous drone contest
The six-month competition was launched in January and is said to carry a $100 million award.
SpaceX and its AI subsidiary xAI are reportedly competing in a new Pentagon prize challenge focused on autonomous drone swarming technology, as per a report from Bloomberg News.
The six-month competition was launched in January and is said to carry a $100 million award.
Bloomberg reported that SpaceX and xAI are among a select group invited to participate in the Defense Department’s effort to develop advanced drone swarming capabilities. The goal is reportedly to create systems that can translate voice commands into digital instructions and manage fleets of autonomous drones.
Neither SpaceX, xAI, nor the Pentagon’s Defense Innovation Unit has commented on the report, and Reuters said it could not independently verify the details.
The development follows SpaceX’s recent acquisition of xAI, which pushed the valuation of the combined companies to an impressive $1.25 trillion. The reported competition comes as SpaceX prepares for a potential initial public offering later this year.
The Pentagon has been moving to speed up drone deployment and expand domestic manufacturing capacity, while also seeking tools to counter unauthorized drone activity around airports and major public events. Large-scale gatherings scheduled this year, including the FIFA World Cup and America250 celebrations, have heightened focus on aerial security.
The reported challenge aligns with broader Defense Department investments in artificial intelligence. Last year, OpenAI, Google, Anthropic, and xAI secured Pentagon contracts worth up to $200 million each to advance AI capabilities across defense applications.
Elon Musk previously joined AI and robotics researchers in signing a 2015 open letter calling for a ban on offensive autonomous weapons. In recent years, however, Musk has spoken on X about the strengths of drone technologies in combat situations.
Starlink restrictions are hitting Russian battlefield comms: report
Tesla Korea hiring AI Chip Engineers amid push for high-volume AI chips
