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.
I’d love to hear from you! If you have any comments, concerns, or questions, please email me at joey@teslarati.com. You can also reach me on Twitter @KlenderJoey, or if you have news tips, you can email us at tips@teslarati.com.
News
Tesla intertwines FSD with in-house Insurance for attractive incentive
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla intertwined its Full Self-Driving (Supervised) suite with its in-house Insurance initiative in an effort to offer an attractive incentive to drivers.
Tesla announced that its new Safety Score 3.0 will automatically have a perfect score of 100 with every mile driven with Full Self-Driving (Supervised) enabled.
The change is designed to boost customers’ average safety scores and deliver noticeably lower monthly premiums.
The move marks the clearest link yet between Tesla’s autonomous driving technology and its proprietary insurance product. Tesla Insurance already relies on real-time vehicle data—such as acceleration, braking, following distance, and speed—to calculate a Safety Score between 0 and 100. Higher scores have long translated into cheaper rates.
Under the previous system, however, even brief manual interventions could drag down the average, frustrating owners who rely heavily on FSD. Version 3.0 eliminates that penalty for supervised autonomous miles, effectively treating FSD-driven segments as the safest possible driving behavior.
The incentive is immediate and financial. Drivers who keep FSD engaged for the majority of their trips will see their overall score rise, potentially shaving hundreds of dollars off annual premiums.
Tesla framed the update as a direct response to customer feedback, many of whom had complained that the old scoring model punished the very behavior it was meant to encourage.
For now, the program applies only to new policies in six states: Indiana, Tennessee, Texas, Arizona, Virginia, and Illinois.
Existing policyholders are not yet included, a point that drew swift questions from the Tesla community. Many owners in other states, including California and Georgia, expressed hope that the benefit would expand nationwide soon.
The announcement arrives as Tesla continues to roll out FSD Supervised updates and push for regulatory approval of more advanced autonomy. By tying insurance savings directly to FSD usage, the company is putting its own actuarial weight behind the technology’s safety claims.
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla has not disclosed exact premium reductions or the full rollout timeline beyond the six launch states.
Still, the message is clear: the more drivers trust FSD Supervised, the more Tesla Insurance will reward them. In an era when legacy insurers remain cautious about autonomous tech, Tesla is betting that its own data will prove the safest miles are the ones driven hands-free.
Elon Musk
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Tesla has finalized its chip design for AI5, as Elon Musk confirmed today that the new chip has reached the tape-out stage, the final step before mass production.
But in a brief reply on X, Musk clarified Tesla’s AI hardware roadmap, essentially confirming that the new chip will not be utilized for being “enough to achieve much better than human safety for FSD.”
He said that AI4 is enough to do that.
Instead, the AI5 chip will be focused on Tesla’s big-time projects for the future: Optimus and supercomputer clusters.
Musk thanked TSMC and Samsung for production support, noting that AI5 could become “one of the most produced AI chips ever.” Yet, the key pivot came in his direct answer: vehicles no longer need the bleeding-edge silicon.
And thank you to @TaiwanSemi_TSC and @Samsung for your support in bringing this chip to production! It will be one of most produced AI chips ever.
— Elon Musk (@elonmusk) April 15, 2026
Existing AI4 hardware, which is already deployed in hundreds of thousands of HW4-equipped Teslas, delivers safety metrics superior to human drivers for Full Self-Driving. AI5 will instead accelerate Optimus robot development and massive Dojo-style training clusters.
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Now, with AI4 proving sufficient, the company avoids costly retrofits across its fleet while redirecting next-generation compute toward higher-value applications: dexterous robots and exponential training scale.
But is it reasonable to assume AI4 enables unsupervised self-driving? Yes, but with important caveats.
On the hardware side, the claim is credible. Tesla’s FSD stack runs end-to-end neural networks trained on billions of miles of real-world data. Internal safety data reportedly shows AI4-equipped vehicles already outperforming average human drivers by a significant margin in controlled metrics (collision avoidance, reaction time, edge-case handling).
Dual-redundant AI4 chips provide ample headroom for the driving task, leaving bandwidth for future model improvements without new silicon. Musk’s assertion aligns with Tesla’s pattern of over-provisioning compute early, then optimizing ruthlessly, exactly as HW3 once sufficed before HW4 scaled further.
Optimus and our supercomputer clusters.
AI4 is enough to achieve much better than human safety for FSD.
— Elon Musk (@elonmusk) April 15, 2026
Unsupervised autonomy, meaning Level 4 or higher, is not solely a compute problem. Regulatory approval remains the primary gate.
Even if AI4 achieves “much better than human” safety statistically, agencies like the NHTSA demand exhaustive validation, liability frameworks, and public trust.
Tesla’s supervised FSD has shown rapid gains in recent versions, yet real-world edge cases, like construction zones, emergency vehicles, and adverse weather, still require driver intervention in many jurisdictions. Competitors like Waymo operate limited unsupervised fleets, but only in geofenced areas with extensive mapping. Tesla’s vision-only, fleet-scale approach is more ambitious—and harder to certify globally.
In short, Musk’s post is both pragmatic and bullish. AI4 is likely capable of unsupervised FSD from a technical standpoint. Whether regulators and consumers agree, and how quickly, will determine if Tesla’s bet pays off.
The company’s capital-efficient path keeps existing cars relevant while pouring future compute into robots. If the safety data holds, unsupervised autonomy could arrive sooner than many expect.
Elon Musk
Elon Musk signals expansion of Tesla’s unique side business
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
Elon Musk has signaled an expansion of Tesla’s unique side business, something that really has nothing to do with cars or spaceships, but fans of the company have truly adopted it as just another one of its awesome ventures.
Musk confirmed on Wednesday that Tesla would build a new Diner location in Palo Alto, Northern California. After hinting last October that it “probably makes sense to open one near our Giga Texas HQ in Austin and engineering HQ in Palo Alto,” it seems one of those locations is being set into motion.
Sure
— Elon Musk (@elonmusk) April 15, 2026
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
He first floated broader expansion plans shortly after the LA opening in July 2025, noting that if the prototype succeeded, Tesla would roll out similar venues in major cities worldwide and along long-distance Supercharger routes.
Earlier hints included a confirmed second site at Starbase in Texas, tied to SpaceX operations, underscoring the Diner’s role in enhancing Tesla’s ecosystem behind vehicles.
The Los Angeles location on Santa Monica Boulevard in West Hollywood has served as a high-profile test case. Opened in July 2025 at 7001 Santa Monica Blvd., it features the world’s largest urban Supercharging station with 80 V4 stalls open to all NACS-compatible EVs, over 250 dining seats, rooftop views, and 24/7 service.
The retro-futuristic building replaced a former Shakey’s and quickly became a destination. Tesla reported selling 50,000 burgers in the first 72 days—an average of over 700 daily—drawing crowds with Cybertruck-shaped packaging, breakfast extensions until 2 p.m., and movie screenings.
Palo Alto stands out as a logical next step for several reasons. As Tesla’s longstanding engineering headquarters in the heart of Silicon Valley, the city is home to thousands of Tesla employees, engineers, and executives who could benefit from a convenient, branded gathering spot.
The area boasts high EV adoption rates, dense tech talent, and heavy traffic along key corridors, making a large Supercharger-diner an ideal fit for both daily commuters and long-haul travelers.
Proximity to Stanford University and the innovation ecosystem would amplify its appeal, potentially serving as a showcase for Tesla’s vision of integrated mobility and lifestyle experiences. It could be a great way for Tesla to recruit new talent from one of the country’s best universities.
If Tesla and Musk decide to move forward with a Palo Alto diner, it would build directly on the LA prototype’s momentum while addressing Musk’s earlier calls for expansion near core Tesla hubs.
Whether it materializes as a full confirmation or evolves from these hints remains to be seen, but the pattern is clear: Tesla is testing ways to make charging stops memorable. For EV drivers and enthusiasts alike, a Silicon Valley outpost could blend cutting-edge tech with nostalgic comfort, further embedding Tesla into everyday culture. As Musk’s comments suggest, the future of the Diner looks promising.
Tesla intertwines FSD with in-house Insurance for attractive incentive
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
