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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.

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.

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“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.

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“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 rolling out Robotaxi pilot in SF Bay Area this weekend: report

Similar to the Austin pilot, the Robotaxi rides will reportedly be a paid service.

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Credit: @AdanGuajardo/X

Tesla is reportedly preparing to launch a Robotaxi pilot program in the Bay Area this weekend, with invites to a select number of customers reportedly being sent out as early as this Friday.

The update was shared in a report from Insider, which cited an internal memo from the electric vehicle maker.

New Robotaxi service launch

According to Insider, the Robotaxi service in the Bay Area is set to launch as soon as Friday. Thus, some Tesla owners in the area should receive invites to use the driverless ride-hailing service. Similar to the Austin pilot, the Robotaxi rides will reportedly be a paid service.

The publication noted that the Robotaxi service’s geofence in its Bay Area launch will be quite large, as it will include Marin, much of the East Bay, San Francisco, and San Jose. This is not surprising as California has long been saturated with Teslas, and it is home to several of the electric vehicle maker’s key facilities.

Unlike the Austin pilot, the Tesla Robotaxi service’s pilot in the Bay Area will use safety drivers seated in the driver’s seat. These drivers will be able to manually take over using the steering wheel and brakes as needed. As per a spokesperson from the California DMV, the agency recently met with Tesla but the company is yet to submit a formal application to operate fully driverless cars. 

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Tesla Robotaxi expansion

Interestingly enough, Tesla did tease the release of its Robotaxi service to the Bay Area in its second quarter earnings call. While discussing the service, Tesla VP of Autopilot/AI Software Ashok Elluswamy mentioned that the company will initially be rolling out Robotaxis with safety drivers in the San Francisco Bay Area. He did, however, also highlight that the electric vehicle maker is working hard to get government permission to release the service for consumers.

“The next thing to expand would be in the San Francisco Bay Area. We are working with the government to get approval here and, in the meanwhile, launch the service without the person in the driver seat just to expedite and while we wait for regulatory approval,” he stated.

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Tesla is ready with a perfect counter to the end of US EV tax credits

Tesla executives have mentioned that these more affordable models would resemble the company’s current lineup.

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Credit: Tesla Asia/X

The United States’ electric vehicle tax credit is coming to an end at the end of the third quarter. Tesla, the country’s leading electric vehicle maker, is ready to meet this challenge with a rather simple but clever counter. 

Tesla executives outlined this strategy in the recently held Q2 2025 earnings call.

End of the US EV tax credit

While Elon Musk has always maintained that he prefers a market with no EV tax credit, he also emphasized that he supports the rollback of any incentives given to the oil and gas industry. The Trump administration has not done this so far, instead focusing on the expiration of the $7,500 EV tax credit at the end of the third quarter.

Tesla has been going all-in on encouraging customers to purchase their vehicles in Q3 to take advantage of lower prices. The company has also implemented a series of incentives across all its offerings, from the Cybertruck to the Model 3. This, however, is not all, as the company seems to be preparing a longer-term solution to the expiration of the EV tax credit.

Affordable variants

During the Q2 2025 earnings call, Vice President of Vehicle Engineering Lars Moray stated that Tesla really did start the production of more affordable models in June. Quality builds of these vehicles are being ramped this quarter, with the goal of optimizing production over the remaining months of the year. If Tesla is successful, these models will be available for everyone in Q4. 

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“We started production in June, and we’re ramping quality builds and things around the quarter. And given that we started in North America and our goal is to maximize production with a higher rate. So starting Q3, we’re going to keep pushing hard on our current models to avoid complexity… We’ll be ready with new, more affordable models available for everyone in Q4.,” Moravy stated. 

These comments suggest that Tesla should be able to offer vehicles that are competitively priced even after the EV tax credit has been phased out. Interestingly enough, previous comments from Tesla executives have mentioned that these more affordable models would resemble the company’s current lineup. This suggests that the more affordable models may indeed be variations of the Model Y and Model 3, but offered at a lower price.

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Elon Musk reveals Tesla’s next Robotaxi expansion in more ways than one

Tesla Robotaxi is growing in more ways than one. Tesla wants to expand and hopes to reach half the U.S. population by the end of the year.

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Credit: Tesla

Tesla CEO Elon Musk revealed the company’s plans for its next expansion of the Robotaxi in terms of both the geofence in Austin and the platform overall, as it looks to move to new areas outside of Texas.

Tesla launched the Robotaxi platform last month on June 22, and has since expanded both the pool of users and the area that the driverless Model Y vehicles can travel within.

The first expansion of the geofence caught the attention of nearly everyone and became a huge headline as Tesla picked a very interesting shape for the new geofence, resembling male reproductive parts.

The next expansion will likely absolve this shape. Musk revealed last night that the new geofence will be “well in excess of what competitors are doing,” and it could happen “hopefully in a week or two.”

Musk’s full quote regarding the expansion of the geofence and the timing was:

“As some may have noted, we have already expanded our service area in Austin. It’s bigger and longer, and it’s going to get even bigger and longer. We are expecting to greatly increase the service area to well in excess of what competitors are doing, hopefully in a week or two.”

The expansion will not stop there, either. As Tesla has operated the Robotaxi platform in Austin for the past month, it has been working with regulators in other areas, like California, Arizona, Nevada, and Florida, to get the driverless ride-hailing system activated in more U.S. states.

Tesla confirmed that they are in talks with each of these states regarding the potential expansion of Robotaxi.

Musk added:

“As we get the approvals and prove out safety, we will be launching the autonomous ride-hailing across most of the country. I think we will probably have autonomous ride-hailing in probably half the population of the US by the end of the year.”

We know that Tesla and Musk have been prone to aggressive and sometimes outlandish timelines regarding self-driving technology specifically. Regulatory approvals could happen by the end of the year in several areas, and working on these large metros is the best way to reach half of the U.S. population.

Tesla said its expansion of the geofence in Austin is conservative and controlled due to its obsession with safety, even admitting at one point during the Earnings Call that they are being “paranoid.” Expanding the geofence is necessary, but Tesla realizes any significant mistake by Robotaxi could take it back to square one.

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