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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 gives HW3 owners another massive update

It was an “at last” moment for HW 3 owners, who have waited for an update on the capabilities of their vehicles for some time. After CEO Elon Musk finally admitted last week that the HW3 vehicles would not be capable of unsupervised FSD, it appears Tesla is bringing a new, more transparent tone to those owners.

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Credit: Tesla Asia/Twitter

Tesla is giving Hardware 3 vehicle owners another massive update, the second major communication the company has given to those drivers after what seemed like years of being left out to dry.

The company, which plans to launch a Full Self-Driving version 14 iteration that is compatible with these cars, which have older chips, is now planning to expand the rollout of the v14 Lite offering to other markets, it said on X.

Tesla said:

“Following future rollout of FSD V14 Lite for HW3 vehicles in the US, we plan on expanding V14 Lite to additional international markets. This update ensures that HW3 vehicle owners will continue to benefit from ongoing software updates. Since international rollout is subject to several factors (completion of technical verification, regional adaptation & relevant regulatory approvals), we can’t provide definitive dates at the moment, but will provide updates on a rolling basis.”

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This announcement comes at a critical time for HW3 owners, many of whom purchased Full Self-Driving (FSD) capability years ago with promises of ongoing support and future-proofing.

HW3, introduced in 2019, powers vehicles from roughly 2019 to early 2023 models. While newer AI4 hardware has advanced rapidly, HW3 owners have felt increasingly left behind, with their last major update stuck around version 12.6 since early 2025.

It was an “at last” moment for HW 3 owners, who have waited for an update on the capabilities of their vehicles for some time. After CEO Elon Musk finally admitted last week that the HW3 vehicles would not be capable of unsupervised FSD, it appears Tesla is bringing a new, more transparent tone to those owners.

V14 Lite represents a significant optimization effort. Tesla has confirmed it will bring many core features of the full V14 release, currently running on more powerful hardware, to the more constrained HW3 platform.

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Expected capabilities include improved handling of complex urban scenarios, better reverse driving, enhanced parking features, and smoother overall autonomy, albeit in a “lite” form tailored to HW3’s compute limits. Tesla’s head of Autopilot, Ashok Elluswamy, noted during the Q1 2026 earnings call that the update is targeted for late June in the U.S.

Tesla is releasing a modified version of FSD v14 for Hardware 3 owners: here’s when

The international expansion is particularly meaningful for owners in Europe, Asia, Australia, and other regions where FSD rollout has lagged due to regulatory hurdles.

Tesla emphasized that timing remains fluid, dependent on “technical verification, regional adaptation & relevant regulatory approvals.” No firm dates were provided, but the company pledged rolling updates as milestones are achieved.

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This move addresses growing concerns that Tesla might abandon legacy hardware. With the recent admission that its capabilities are limited and not capable of Tesla’s grand autonomy ambitions, owners are finally in the light of truth, with more honesty being put forth as the company navigates this chapter.

For Tesla, keeping HW3 relevant strengthens customer loyalty and protects the value of older vehicles. It also buys time as the company pushes toward broader regulatory approvals and unsupervised autonomy on newer platforms.

While V14 Lite isn’t the full unsupervised experience once promised, it delivers tangible improvements and signals that HW3 owners are not being forgotten.

As Tesla continues its rapid AI and autonomy evolution, this update underscores a key principle: software can breathe new life into existing hardware. For tens of thousands of HW3 drivers worldwide, V14 Lite could mark the beginning of a renewed era of confidence in their vehicles.

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SpaceX Board has set a Mars bonus for Elon Musk

SpaceX has given Elon Musk the goal to put one million people on Mars.

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Rendering of a colonized Mars by way of SpaceX

SpaceX’s board approved a compensation plan for Elon Musk that ties his pay directly to colonizing Mars and building data centers in outer space. The details surfaced this week after Reuters reviewed SpaceX’s confidential registration statement filed with the Securities and Exchange Commission, making it one of the first concrete looks inside the company’s financials ahead of a public offering.

The pay package will reportedly award Musk 200 million super-voting restricted shares if the company hits a market valuation milestone, with the most ambitious targets going further. To unlock the full award, SpaceX would need to reach a $7.5 trillion valuation and help establish a permanent human settlement on Mars with at least one million residents. Additional incentives are tied to developing space-based computing infrastructure capable of delivering at least 100 terawatts of processing power.

SpaceX wins its first MARS contract but it comes with a catch

Long before SpaceX filed anything with the SEC, Elon Musk had already spent years framing Mars colonization as an insurance policy against human extinction. The philosophy traces back to at least 2001, when Musk first began researching Mars missions independently, before SpaceX even existed. By 2002 he had founded the company with Mars as the stated long-term goal.

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In a 2017 presentation at the International Astronautical Congress, Musk outlined the specific vision that still underpins SpaceX’s architecture today. He described a self-sustaining city on Mars requiring roughly one million people to become viable, the same number now written into his compensation package.

SpaceX’s Starship, still in active development, was designed from the ground up to support the eventual colonization of Mars. Musk has stated publicly that getting the cost per ton to Mars below $100,000 is necessary to make mass migration economically feasible. Everything from Starship’s payload capacity to its full reusability targets flows from that single constraint. One can say that Musk’s latest compensation package has put a formal valuation on Mars for the first time.

SpaceX is targeting an IPO around June 28, Musk’s birthday, at a valuation of approximately $1.75 trillion. Between the Mars rover contract, the Golden Dome software group, Space Force satellite launches, and now a pay structure built around interplanetary colonization, SpaceX has become the single most consequential contractor in American space and defense. The IPO will put a public price tag on all of it for the first time.

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Tesla’s biggest rivals fights charging wait times with a modern approach

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Tesla V4 Supercharger installation ramping in Europe

Earlier this week, we wrote a story on how Tesla is launching a new Supercharging Queue system to mitigate problems between drivers when there is a wait to charge.

Rather than potentially having people end up in a physical conflict, Tesla’s approach is to determine who is next to charge based on geographic data.

Tesla launches solution to end Supercharger fights once and for all

But some companies, notably Tesla’s biggest rival in China, BYD, are taking a different approach, focusing on charging speeds rather than how they will manage delays.

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BYD’s approach, especially with its tests of ultra-fast “Flash Charging” technology, is to eliminate the length of a charging session. At the heart of this strategy is BYD’s second-generation Blade Battery paired with 1,500-kW Flash Chargers.

Unveiled earlier this year, the system charges compatible vehicles from 10 percent to 70 percent state of charge in just five minutes and from 10 percent to 97 percent in nine minutes.

Real-world demonstrations on models like the Yangwang U7 and Denza Z9 GT have shown the tech delivering roughly 250 miles (400 kilometers) of range in just five minutes. This would essentially match or beat the time it takes to fill a gas tank.

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Sometimes, gas pumps get congested, and there are lines. You rarely see conflicts at pumps because filling up a tank rarely takes more than five minutes.

Tesla’s fastest Supercharger build currently is the v4, which can deliver up to 325 kW for Cybertruck and 250 kW for other models, but there are “true” sites that are capable of up to 500 kW. This enables speeds of up to 1,000 miles per hour, or 1,400 miles for 350 kW-capable vehicles.

The breakthrough stems from BYD’s vertically integrated ecosystem: a new 1,000-volt architecture, 10C charging rates, and proprietary silicon-carbide chips that minimize internal resistance while protecting battery health.

The company plans to install 20,000 Flash Charging stations across China by the end of 2026, with thousands already operational and global expansion eyed for Europe and beyond later this year.

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Early rollout targets popular models, including upgrades to high-volume sellers like the Seal and Sealion series, bringing five-minute charging to mainstream prices around 100,000 yuan (about $14,000).

This approach contrasts sharply with Tesla’s software solution. Tesla’s Virtual Queue uses geofencing and the app to assign turns at crowded sites, addressing driver disputes and idle time. It’s a clever fix for today’s network realities.

Yet, BYD’s philosophy is simpler: make charging so fast that waits barely exist. A five-minute stop becomes as convenient as a gas-station visit, reducing station dwell time, easing grid strain, and lowering range anxiety for long trips.

For consumers, the difference is potentially tangible. They’ll spend more time driving and less time parked. It is just another way Tesla and BYD are pushing one another to improve the overall experience of EV ownership.

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