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Tesla introduces Safety Score (Beta) system that incentivizes safe driving
As Tesla starts the rollout of its “Request Full Self Driving” button to more members of its fleet, the company has also introduced its Safety Score (Beta) system to evaluate driving behaviors. With this new system on hand, Tesla has effectively incentivized and gamified safe driving, which would likely make the rollout of programs such as FSD Beta a lot smoother and less likely to result in accidents.
Safety Scores are an assessment of driving behavior based on five metrics that the company calls “Safety Factors.” These factors are Forward Collision Warnings (FCW) per 1,000 Miles, Hard Braking, Aggressive Turning, Unsafe Following, and Forced Autopilot Disengagement. Tesla utilizes a Predicted Collision Frequency (PCF) formula based on statistical modeling using 6 billion miles of fleet data to predict how many collisions may occur per 1 million miles driven. The PCF is converted into a Safety Score between 0 and 100, which are then viewed through the Tesla App.

Tesla released some tips on how drivers could improve their Safety Score. To improve ratings on Forward Collision Warnings per 1,000 Miles, drivers are advised to maintain a following distance that gives enough time to react to slower or stationary vehicles ahead. Hard Braking scores, on the other hand, could be improved by engaging the brake pedal early when slowing down and using regen braking whenever possible and safe to do so. Hard Braking scores should also improve when drivers maintain a safe distance from the vehicle in front of them.
Aggressive Turning is defined as left/right acceleration in excess of 0.4g. Thus, drivers could improve their numbers in this metric by taking turns gradually, reducing their speed heading into a turn, and gradually accelerating afterward. Unsafe Following scores would likely be easy to improve, as drivers simply need to maintain a following distance worth several car lengths to the vehicle in front. This way, drivers could have enough time to react just in case something untoward happens.
Forced Autopilot Disengagement highlights the need to use the company’s advanced driver-assist features in a responsible manner. Proper Autopilot use is outlined in vehicles’ Owner’s Manual, and it requires drivers to have their hands on the wheel and pay close attention to the road. Tesla notes that the Forced Autopilot Disengagement metric is a 1 or 0 indicator, with the value being 1 if Autopilot forcibly disengages during a drive and 0 if the system is operated nominally.
- An example of a high Safety Score, reflecting generally good driving behaviors. (Credit: Jason DeBolt/Twitter)
- An example of a low Safety Score, reflecting some unsafe driving behaviors. (Credit: Tesla Raj/Twitter)
Safety Scores are updated every time a trip is taken on a Tesla vehicle. Provided that a Tesla is connected to the internet, Safety Scores should provide immediate feedback on a driving session. Vehicles that are not connected to the internet would update their Safety Scores as soon as cellular connectivity is secured. It should also be noted that all trips over 0.1 miles are considered as a valid driving session that could affect a driver’s rating.
Safety Scores are vehicle-specific as well, so drivers with multiple Teslas could have varying ratings for each of their cars. Lastly, Safety Scores should reset when a vehicle is sold, which means that a Tesla’s new owner should not be affected by the ratings of the previous driver. Drivers could also not carry over their Safety Scores from one vehicle if they purchase a new Tesla.
A full and extensive discussion of how Tesla’s Safety Scores work could be found here.
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Tesla crosses major Unsupervised Self-Driving milestone
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.
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Tesla Robotaxi will be a 24/7 service: here’s when
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.
News
Tesla Full Self-Driving will now overtake manual driving to avoid disaster
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.

