News
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.
Tesla rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.
Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.
Tesla Full Self-Driving v14.3.5 Performance
The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.
Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.
We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.
FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:
🚨 Tesla Full Self-Driving v14.3.5 takes a wide turn as flagger crews set up signage for the day https://t.co/3v0PL9qhlI pic.twitter.com/i4CKqxE16c
— TESLARATI (@Teslarati) July 13, 2026
Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:
🚨 Tesla Full Self-Driving v14.3.5 backs up for an oncoming tractor trailer taking a wide turn https://t.co/0WuAqNMpRR pic.twitter.com/s6yZGVm5Te
— TESLARATI (@Teslarati) July 13, 2026
X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:
“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”
Check it out here:
Rapidfire epic moments on FSD V14.3.5
1) FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.
2) Insane speed to vehicle cues. As FSD approaches… pic.twitter.com/bSnySSlFHR
— Mike P (@mikepat711) July 13, 2026
It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.
Terrible Parking
Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:
Horrible first impression v14.3.5 on my 2025 Tesla Model 3 LR RWD Premium 😭
3 terrible parking jobs in 23 min including parking on a ramp in a business park & parking perpendicular out in the road on street only parking situation.
Wish I had a better drive but I still believe… pic.twitter.com/TtyhRHAFG7
— David Moss (@DavidMoss) July 13, 2026
New Features
Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:
🚨 Here’s the new Camera Preview feature on FSD v14.3.5 pic.twitter.com/OodfZgDppy
— TESLARATI (@Teslarati) July 13, 2026
Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.
Lifestyle
Tesla makes the cut on California’s newest EV Rebate program
California just signed a $270 million EV rebate into law and it starts this summer.
California Governor Gavin Newsom signed SB 168 into law on Monday, July 13, 2026, creating a $270 million EV rebate program that delivers money directly at the dealership rather than as a tax credit applied months later. The program, called MyFirstEV, is funded equally by California’s state budget and participating automakers, with each contributing $135.5 million to make the math work.
The timing is directly tied to the loss of federal support when the $7,500 federal EV tax credit ended, removing the most significant consumer incentive that had driven EV adoption in the U.S. California, which accounts for roughly one-third of all EVs sold nationally, moved to fill that gap with a state-level replacement.
The rebate structure is straightforward. First-time EV buyers can receive $3,500 off any new battery-electric vehicle with an MSRP up to $50,000. Used EVs priced at $25,000 or below qualify for a $1,750 rebate. The credit is applied at the point of sale, which removes the friction of the old federal system where buyers had to wait for tax season to see the benefit. The program goes live later this summer, with the California Air Resources Board expected to release full participation details next month.
California hits Tesla Cybercab and Robotaxi driverless cars with new law
For Tesla buyers, the implications are mixed. The Tesla Model 3 RWD at $42,490 and the Model 3 Long Range at $47,490 both fall under the $50,000 cap and would qualify for the full $3,500 rebate for first-time buyers. The Model Y, which starts at $44,990 after Tesla’s recent price adjustment, also qualifies. The Model X, Model S, and Cybertruck all exceed the cap and receive no benefit. As Teslarati has reported, the program also includes a carve-out exempting California-based automakers like Rivian and Lucid from the price cap entirely, a provision that puts Tesla at a disadvantage since it relocated its headquarters to Texas in 2021.
Other qualifying vehicles include the Chevrolet Equinox EV, Ford Mustang Mach-E, Hyundai Ioniq 5, Kia EV6, and Volkswagen ID.4.
The Tesla Semi is entering a new Pilot Program with Paper Transport, LLC (PTI), a Wisconsin-based transportation provider. The company will test the Semi’s Long Range configuration through “dedicated operations within the Chicago market.”
Chicago presents an interesting challenge for the Semi, as it will be a colder-weather climate that will test the Semi’s ability to operate in lower temperatures and in potentially large accumulations of snow. This is something Tesla has been testing with the Semi in Alaska and even in Northern California during the colder months, but Chicago will present a truly tough midwestern winter.
Tesla Semi spotted on journey home after winter performance testing
PTI says it is using the Semi to evaluate its strategy of reducing transportation emissions while maintaining performance, reliability, and cost efficiency. These are major arguments for the Semi being introduced into new fleets.
CEO of PTI Tyler Ellison said:
“PTI has been a leader in sustainable transportation solutions for over 15 years. We take a consultative approach to helping customers identify and implement the right transportation solution for their network. Our partnership with Tesla expands our portfolio alongside renewable natural gas and intermodal, giving customers more ways to reduce Scope 3 emissions without compromising service or economics.”
PTI is far from the first company to adopt the Semi within a fleet, as Tesla entered strategic agreements with PepsiCo. and its subsidiary Frito-Lay for a Pilot Program that extended throughout the California region.
Tesla has let companies like those utilize the Semi to determine whether it would be suitable for their operations. Additionally, Tesla gets valuable information regarding the Semi’s performance, knowing what to improve and what is ideal for companies that will utilize the all-electric truck for regional and nationwide logistics.
PTI plans to utilize the Long Range configuration, which is priced at $290,000 and features a range of approximately 500 miles, a three-motor powertrain, up to 800 kW of drive power, and consumption of just 1.7 kWh per mile.
Tesla Semi pricing revealed after company uncovers trim levels
VP of Maintenance at PTI, Bryan Ellen, added:
“We are excited to partner with Tesla, leveraging their ever-evolving technology. We are bullish in our estimation of the parallels available between our dedicated model and the efficiency of their fully electric Class 8 tractor. We anticipate a growing synergy between our businesses as we work to facilitate this sustainable solution for our customers.”
PTI has logged more than 87 million miles using sources like compressed and renewable gas, but now is looking to take it a step further with fully electric operations.
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
Tesla makes the cut on California’s newest EV Rebate program
