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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.

“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.

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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.

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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 Roadster event gets delayed due to unfavorable weather

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Credit: Tesla

Tesla is delaying its event for the Roadster, moving it from this Thursday, October 1, to Thursday, October 15, due to unfavorable weather.

The company has said it has been tracking the weather for this Thursday closely with local meteorologists, and because the event can only be held outside, Tesla is making the call to delay it:

“We’ve been tracking the weather closely with local meteorologists, but given the severe conditions predicted & because this event can only be held outdoors, we’ve made the difficult decision to reschedule. New date is October 15. Additional details to follow.”

We are sure that this is bringing back PTSD for some Tesla fans, and we know it is not ideal, but this also reveals some things about the event. Tesla said that this can only be held outdoors, meaning it bodes well for the rumors that the vehicle could potentially hover.

Some believe that this was essentially confirmed by the FAA airspace restriction they were granted, but this could have been for a drone show or to keep drones from spying on the event.

Tesla Roadster is available for order once again following brief hold

The Roadster event has been long-awaited, and it is unfortunate that the weather is going to keep us all waiting a little bit longer.

The Tesla Roadster will be unveiled in Waco, Texas.

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SpaceX turned a heralding moment for Starship into its greatest

Starship reached orbit despite losing an engine, deployed 26 Starlink V3 satellites on Flight 14.

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SpaceX’s Starship reached orbit for the first time on Monday, and for a few nail-biting minutes it looked like it wouldn’t. During ascent on Flight 14, one of Ship 41’s six Raptor engines shut down early, and SpaceX’s livestream host Dan Huot told viewers the team had decided not to commit to orbit. Minutes later, after what Huot described as a lot of conversation in the control room, the final poll came back in favor, and a roughly 19 second burn of a single Raptor pushed the ship into orbit about 170 miles up.

The reversal matters because SpaceX had written the exit ramp into the mission plan. The company said it would only fire the orbital insertion burn if flight controllers confirmed enough backup hardware remained for the deorbit burn, a condition Teslarati laid out ahead of the flight. Losing an engine was exactly the scenario that rule was built for.

Pressing forward fits Elon Musk’s history. Falcon 1 failed three straight times before its fourth launch reached orbit in 2008, with SpaceX nearly out of money, and Starship was developed by flying prototypes until they broke. What changed this year SpaceX going public, and with $SPCX sliding below its IPO price in July when Flight 13 slipped, the short interest climbed significantly, as Teslarati reported at the time. A Starship potentially lost today with revenue generating next-gen Starlink satellites aboard would have landed directly on shareholders.

That pressure showed up after orbit. SpaceX cut a flight planned to last nearly 10 hours to about three, moving splashdown from west of Chile to the North Pacific near Hawaii. SpaceX gave no reason, though Musk said this month the company was being extremely cautious about debris risk. The single Raptor for deorbit worked, and Ship 41 completed its flip and landing burn before breaking apart in the water, an outcome SpaceX expected. Musk has structured SpaceX’s governance to shield long term bets from market pressure.

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The payload is the bigger business story. Musk posted that all 26 Starlink V3 satellites deployed and are “operating nominally.” Each V3 is rated for about 1 Tbps of downlink and 160 Gbps of uplink, so this single launch adds roughly 26 Tbps, about 10 times what a Falcon 9 load of V2 Mini satellites adds. The V3 is too large for Falcon 9, making Starship the only vehicle that can build out the planned 100,000 satellite constellation, at up to 60 per flight once it reaches routine service. Unlike the 20 V3 units on Flight 13, which reentered on a suborbital path, these will raise their orbits and could begin serving customers within weeks and bring in hundreds of millions of additional dollars in projected Starlink revenue.

SpaceX has already begun winding down Falcon 9 Starlink launches from Florida in favor of Starship. Reported targets put Flight 15 as early as October 19, leaving about three weeks to diagnose Monday’s engine shutdown before the next orbital attempt.

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Tesla Cybercab fleet doubles to well over 100 units

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(Credit: Teslarati)

Tesla quietly doubled the size of its Cybercab fleet within the Robotaxi program in Austin, Texas, over the weekend to well over 100 units.

The move not only establishes more of the steering-wheel-less and pedal-less vehicles within the ride-sharing fleet Tesla has been operating for a year, but it also solidifies a more robust Robotaxi fleet as a whole.

Riders started receiving notifications from the Robotaxi app that stated: “Cybercab fleet has doubled: more rides available.”

Tesla first launched rides in the Cybercab in early September, although the Robotaxi fleet has been active for over a year, as rides began last Summer. Cybercab is truly Tesla’s most crucial vehicle release yet, as it is the first car any company has built that is geared toward full-fledged and end-to-end autonomy, never needing human intervention for anything.

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Only available in Austin at the current time, Cybercab has two seats and has been spotted testing around various U.S. states and regions; Tesla plans to deploy the Cybercab in various U.S. cities in the coming months as a best-case scenario.

Tesla Cybercab gets initial tie-in to localized, in-house cathode plant

The availability of the Cybercab has doubled from just 58 units last Monday to 125 the following Friday. Marking a substantial increase in Cybercab availability, the additional ride-sharing units are more than welcome, as wait times for Cybercabs, especially, were quite high.

The dramatic increase is a sign that demand for Robotaxi is growing and Tesla is feeling more confident that its driverless ride-hailing suite, especially its Full Self-Driving software, is able to handle any traffic situation without explicit direction or supervision from a human being.

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