The Insurance Institute for Highway Safety (IIHS) tested Tesla Autopilot safeguards and found that drivers are pretty quick to adapt to the windows of opportunity the suite gives after warning them to pay attention.
The IIHS study sought to determine whether partially automated driving systems and their safeguards increase driver attentiveness. With the rollout of more advanced driver assistance systems (ADAS) and semi-autonomous driving functionalities, the goal is to increase safety.
However, these suites still require the driver to pay attention and be aware of any potential opportunity to take over if needed. These driving systems and features are designed to increase safety but still require the driver’s full attention, hence their semi-autonomous label.
Credit: Tesla
For the study, the IIHS tested both Tesla Autopilot safeguards and those available in Volvo’s Pilot Assist.
The study gave 14 drivers a month with a 2020 Tesla Model 3 and required them to travel on Autopilot, when available, over one month. The IIHS wanted to see how drivers behaved leading up to, during, and after attention reminders prompted by a lack of focus on their end.
The Autopilot study found that drivers could learn safeguard sequences and identify “windows of opportunity” to perform non-driving-related tasks. These vehicles still utilized an Autopilot nag and a torque sensor to monitor whether the driver was paying attention. Failure to keep hands on the steering wheel would result in attention reminders.
Failure to change after the reminders would result in suspension of the Autopilot system, commonly referred to as “Autopilot jail.”
The study found:
“In total, the volunteers drove a little more than 12,000 miles with Autopilot engaged. During that time, they triggered 3,858 attention-related warnings from the partial automation system. About half of those alerts occurred when they had at least one hand on the steering wheel but were apparently not moving it enough to satisfy the torque sensor.”
Most warnings did not go past the initial reminder, and only 72 instances resulted in the driver not responding fast enough to prevent the alerts from escalating.
The study found that while initial warnings increased by 26 percent over the first four weeks, showing drivers were prone to expect it, escalations fell by 64 percent, meaning they did not allow the system to continue warning them.
However, this does not mean that non-driving secondary activities stopped after the first warning. Instead, the study showed something interesting:
“The researchers found that the drivers did nondriving secondary activities, looked away from the road, and had both hands off the wheel more often during the alerts and in the 10 seconds before and after them as they learned how the attention reminders worked. The longer they used the system, the less time it took them to take their hands off the wheel again once the alerts stopped.”
The IIHS admits that the safety impact of the change is hard to measure. While the agency noted that some research shows the longer a driver allows their attention to wander, the more likely they will be involved in an accident, the study also said that “even short lapses of attention become so frequent that the periods of supposed engagement between them have little value.”
The study also said the safeguards can be beneficial to behavior immediately and in the longer term, and other patterns showed potentially unintended consequences:
“The current study has shown that driver interactions with partial automation are dynamic. Some of the changes we observed indicate that system safeguards can beneficially shape behavior both immediately and in the longer term, whereas other patterns revealed potentially unintended consequences. It is important to note that these findings are likely not unique to Tesla’s Autopilot, as many systems on the market have overtly similar safeguard designs. As such, some observations from this study maybe relevant to other driver assistance technology that still requires the driver to be engaged in the driving task.”
IIHS Senior Research Scientist Alexandra Mueller, who led the study, said:
“These results show that escalating, multimodal attention reminders are very effective in getting drivers to change their behavior. However, better safeguards are needed to ensure that the behavior change actually translates to more attentive driving.”
While this study provides evidence that perhaps better safeguards are needed, it is important to note that Tesla has upgraded the in-cabin camera to monitor driver attentiveness.
Tesla activates cabin-facing camera in bid to improve vehicle safety
Additionally, many cars are on the road without these driver assistance and safety features.
Distracted driving is going to occur whether a vehicle is equipped with modern technology or not.
Tesla and other automakers have brought their newest vehicles up to speed in the fight against distracted driving, and perhaps this study showed that warnings could and should come at varying rates to prevent anticipation from drivers.
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Elon Musk
Elon Musk proposes Grok 5 vs world’s best League of Legends team match
Musk’s proposal has received positive reception from professional players and Riot Games alike.
Elon Musk has proposed a high-profile gaming challenge for xAI’s upcoming Grok 5. As per Musk, it would be interesting to see if the large language model could beat the world’ best human League of Legends team with specific constraints.
Musk’s proposal has received positive reception from professional players and Riot Games alike, suggesting that the exciting exhibition match might indeed happen.
Musk outlines restrictions for Grok
In his post on X, Musk detailed constraints to keep the match competitive, including limiting Grok to human-level reaction times, human-speed clicking, and viewing the game only through a camera feed with standard 20/20 vision. The idea quickly circulated across the esports community, drawing commentary from former pros and AI researchers, as noted in a Dexerto report.
Former League pro Eugene “Pobelter” Park expressed enthusiasm, offering to help Musk’s team and noting the unique comparison to past AI-versus-human breakthroughs, such as OpenAI’s Dota 2 bots. AI researcher Oriol Vinyals, who previously reached Grandmaster rank in StarCraft, suggested testing Grok in RTS gameplay as well.
Musk welcomed the idea, even responding positively to Vinyals’ comment that it would be nice to see Optimus operate the mouse and keyboard.
Pros debate Grok’s chances, T1 and Riot show interest
Reactions weren’t universally optimistic. Former professional mid-laner Joedat “Voyboy” Esfahani argued that even with Grok’s rapid learning capabilities, League of Legends requires deep synergy, game-state interpretation, and team coordination that may be difficult for AI to master at top competitive levels. Yiliang “Doublelift” Peng was similarly skeptical, publicly stating he doubted Grok could beat T1, or even himself, and jokingly promised to shave his head if Grok managed to win.
T1, however, embraced the proposal, responding with a GIF of Faker and the message “We are ready,” signaling their willingness to participate. Riot Games itself also reacted, with co-founder Marc Merrill replying to Musk with “let’s discuss.” Needless to say, it appears that Riot Games in onboard with the idea.
Though no match has been confirmed, interest from players, teams, and Riot suggests the concept could materialize into a landmark AI-versus-human matchup, potentially becoming one of the most viewed League of Legends events in history. The fact that Grok 5 will be constrained to human limits would definitely add an interesting dimension to the matchup, as it could truly demonstrate how human-like the large language model could be like in real-time scenarios.
Tesla has passed a key milestone, and it was one that CEO Elon Musk initially mentioned more than nine years ago when he published Master Plan, Part Deux.
As per Tesla China in a post on its official Weibo account, the company’s Autopilot system has accumulated over 10 billion kilometers of real-world driving experience.
Tesla China’s subtle, but huge announcement
In its Weibo post, Tesla China announced that the company’s Autopilot system has accumulated 10 billion kilometers of driving experience. “In this respect, Tesla vehicles equipped with Autopilot technology can be considered to have the world’s most experienced and seasoned driver.”
Tesla AI’s handle on Weibo also highlighted a key advantage of the company’s self-driving system. “It will never drive under the influence of alcohol, be distracted, or be fatigued,” the team wrote. “We believe that advancements in Autopilot technology will save more lives.”
Tesla China did not clarify exactly what it meant by “Autopilot” in its Weibo post, though the company’s intense focus on FSD over the past years suggests that the term includes miles that were driven by FSD (Beta) and Full Self-Driving (Supervised). Either way, 10 billion cumulative miles of real-world data is something that few, if any, competitors could compete with.
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Elon Musk’s 10-billion-km estimate, way back in 2016
When Elon Musk published Master Plan Part Deux, he outlined his vision for the company’s autonomous driving system. At the time, Autopilot was still very new, though Musk was already envisioning how the system could get regulatory approval worldwide. He estimated that worldwide regulatory approval will probably require around 10 billion miles of real-world driving data, which was an impossible-sounding amount at the time.
“Even once the software is highly refined and far better than the average human driver, there will still be a significant time gap, varying widely by jurisdiction, before true self-driving is approved by regulators. We expect that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km). Current fleet learning is happening at just over 3 million miles (5 million km) per day,” Musk wrote.
It’s quite interesting but Tesla is indeed getting regulatory approval for FSD (Supervised) at a steady pace today, at a time when 10 billion miles of data has been achieved. The system has been active in the United States and has since been rolled out to other countries such as Australia, New Zealand, China, and, more recently, South Korea. Expectations are high that Tesla could secure FSD approval in Europe sometime next year as well.
News
Elon Musk’s Boring Company reveals Prufrock TBM’s most disruptive feature
As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
The Boring Company has quietly revealed one of its tunnel boring machines’ (TBMs) most underrated feature. As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
Prufrock 5 leaves the factory
The Boring Company is arguably the quietest venture currently backed by Elon Musk, inspiring far fewer headlines than his other, more high-profile companies such as Tesla, SpaceX, and xAI. Still, the Boring Company’s mission is ambitious, as it is a company designed to solve the problem of congestion in cities.
To accomplish this, the Boring Company would need to develop tunnel boring machines that could dig incredibly quickly. To this end, the startup has designed Prufrock, an all-electric TBM that’s designed to eventually be fast enough as an everyday garden snail. Among TBMs, such a speed would be revolutionary.
The startup has taken a step towards this recently, when The Boring Company posted a photo of Prufrock-5 coming out of its Bastrop, Texas facility. “On a rainy day in Bastrop, Prufrock-5 has left the factory. Will begin tunneling by December 1. Hoping for a step function increase in speed,” the Boring Company wrote.
Prufrock’s quiet disruption
Interestingly enough, the Boring Company also mentioned a key feature of its Prufrock machines that makes them significantly more sustainable and reusable than conventional TBMs. As per a user on X, standard tunnel boring machines are often left underground at the conclusion of a project because retrieving them is usually more expensive and impractical than abandoning them in the location.
As per the Boring Company, however, this is not the case for its Prufrock machines, as they are retrieved, upgraded, and deployed again with improvements. “All Prufrocks are reused, usually with upgrades between launches. Prufrock-1 has now dug six tunnels,” the Boring Company wrote in its reply on X.
The Boring Company’s reply is quite exciting as it suggests that the TBMs from the tunneling startup could eventually be as reusable as SpaceX’s boosters. This is on brand for an Elon Musk-backed venture, of course, though the Boring Company’s disruption is a bit more underground.
Tesla is being accused of infringing robotics patents by a company called Perrone Robotics, which is based out of Charlottesville, Virginia.
The suit was filed in Alexandria, Virginia, and accuses Tesla of knowingly infringing upon five patents related to robotics systems for self-driving vehicles.
The company said its founder, Paul Perrone, developed general-purpose robotics operating systems for individual robots and automated devices.
Perrone Robotics claims that all Tesla vehicles utilizing the company’s Autopilot suite within the last six years infringe the five patents, according to a report from Reuters.
Tesla’s new Safety Report shows Autopilot is nine times safer than humans
One patent was something the company attempted to sell to Tesla back in 2017. The five patents cover a “General Purpose Operating System for Robotics,” otherwise known as GPROS.
The GPROS suite includes extensions for autonomous vehicle controls, path planning, and sensor fusion. One key patent, U.S. 10,331,136, was explicitly offered to Tesla by Perrone back in 2017, but the company rejected it.
The suit aims to halt any further infringements and seeks unspecified damages.
This is far from the first suit Tesla has been involved in, including one from his year with Perceptive Automata LLC, which accused Tesla of infringing on AI models to interpret pedestrian/cyclist intent via cameras without licensing. Tesla appeared in court in August, but its motion to dismiss was partially denied earlier this month.
Tesla also settled a suit with Arsus LLC, which accused Autopilot’s electronic stability features of infringing on rollover prevention tech. Tesla won via an inter partes review in September.
Most of these cases involve non-practicing entities or startups asserting broad autonomous vehicle patents against Tesla’s rapid iteration.
Tesla typically counters with those inter partes reviews, claiming invalidity. Tesla has successfully defended about 70 percent of the autonomous vehicle lawsuits it has been involved in since 2020, but settlements are common to avoid discovery costs.
The case is Perrone Robotics Inc v Tesla Inc, U.S. District Court, Eastern District of Virginia, No. 25-02156. Tesla has not yet listed an attorney for the case, according to the report.
Elon Musk proposes Grok 5 vs world’s best League of Legends team match
Elon Musk’s Boring Company reveals Prufrock TBM’s most disruptive feature
