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OPINION: Tesla’s ‘Safety Score’ Beta needs broader terms for factoring your score
Tesla’s “Safety Score” Beta is one of the most impressive ideas to improve driving safety, in my opinion. An article from Model 3 owner and Tesla enthusiast Nick Howard explained that Tesla is essentially gamifying the act of driving, encouraging owners to drive in a manner that would allow their scores to be higher. If you know anything about the Tesla community, you know that it is filled with die-hard fans who are satirically battling it out for the elusive 100 scores. While Tesla has outlined the ways that driving behaviors could affect the score for better or for worse, I believe that other instances may need to be outlined so owners are perfectly clear on how their score could be affected based on their hobbies or driving style. While I disagree with Consumer Reports’ assumption that the Safety Score is a bad idea (which, in reality, makes no real sense to me), I do believe that some owners are confused on what makes their score higher or lower, especially as many owners are attempting to enter the elusive Full Self-Driving Beta program.
If you’ve taken a peek at Tesla’s Support page that outlines the numerous factors that can affect a driver’s Safety Score, it seems pretty straightforward. There are cut and dry behaviors that tend to be recognized universally as “aggressive,” including tailgating, hard braking, and aggressive turning. Additionally, Forward Collision Warnings per 1,000 miles and forced Autopilot disengagements are also included in the behaviors that could affect your score, but these are exclusive to Tesla, of course, due to their use of Forward Collision Warnings and Autopilot disengagements.
Tesla introduces Safety Score (Beta) system that incentivizes safe driving
It’s very self-explanatory: Drive safely and receive a higher score. But are there not instances where things could get a tad confusing for some drivers, especially those with scores just below the perfect 100 threshold?
One example that I saw over the weekend was from Richard Marrero, a Tesla owner who was curious about taking his vehicle to the local racetrack. While Tesla owners are occasionally hitting the accelerator when a stoplight turns green, it may be understandable for Safety Scores to be affected. However, what if the nature of the driving occurs on a closed circuit? Marrero may drive like a saint on the road but might want to push his vehicle to the limit at a local dragstrip or raceway. After all, why have a high-performance car with face-melting acceleration if you can’t test it from time to time?
Does anyone know if taking my Tesla to a racetrack will hurt my safety score? @elonmusk @SawyerMerritt @DirtyTesla @tesla_raj @Teslarati
— Richard Marrero (@The_Richard_M) October 2, 2021
There are other examples that could affect a Safety Score that are technically out of the driver’s control. In some instances, it may be an action taken by the driver that is technically safer than other options, yet it could reduce the Safety Score. Tesla Joy, a Model 3 owner, encountered this predicament on October 1, according to a Tweet. Her Safety Score was reduced due to hard braking at a “quick changing yellow light.” I believe nearly everyone who has a driver’s license can attest that some stoplights are slightly more accelerated than others. Quick changing yellow lights are one of the most polarizing events in a daily drive. Some will tell you just to run through it, others will argue that the safer thing to do is just slow down and stop. Whichever way you choose to handle this scenario, you are likely to encounter someone who shares a point of view on how to handle the premature yellow light in a different manner.
Today I hard braked for 2 quick changing yellow lights & got dinged. I also sped up at another yellow light and didn’t get dinged but I felt more dangerous that way. Since Tesla car can see?, can hard braking at yellow light be exempt from penalty cuz it’s safer? ? @elonmusk
— Tesla Joy (@TeslaJoy) October 2, 2021
However, I don’t necessarily believe that there is a “wrong” way to handle it. While the right way to do it, according to my knowledge as a driver of over 11 years, would require you to slow down and come to a stop, especially since the yellow light is a key indicator of “slow down.” Tesla Joy did it as most Learner’s Permit booklets would describe, yet she was still docked points.
There are undoubtedly more examples of how Tesla could do a better job of explaining what actions are not favorable for the Safety Score system, and I would love to hear your thoughts or examples on things that have occurred that affected your score. Tesla did a wonderful job of outlining the most face-value actions that Safety Scores will be affected by, but there are other questions that need to be confronted so drivers are clear on what other things could hurt their scores. After all, the wider the FSD Beta testing group is, the more data Tesla will obtain through its Neural Network.
Don’t hesitate to contact us with tips! Email us at tips@teslarati.com, or you can email me directly at joey@teslarati.com.
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.
Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.
Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
