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Tesla rolls out latest Safety Score update—Here’s what’s new
Tesla’s latest Safety Score update drops one highly criticized factor, while adding weight to pieces like speeding, follow distance, and more.
Tesla has officially started rolling out a new version of its insurance program’s Safety Scores beta, improving upon a few different metrics that make up the index.
As detailed on the Tesla Insurance web page, the company has updated its Safety Scores to beta version 2.2 from the previous version 2.1. The update primarily includes improvements to how Excessive Speeding is measured, along with the removal of Forward Collision Warnings (FCW) from the formula.
In addition, Tesla has slightly increased the values of related factors such as Hard Braking and Unsafe Following Time in the v2.2 formula, perhaps in an attempt to help accommodate some of the situations previously covered by the FCW rating.
READ MORE ON TESLA INSURANCE: Tesla launches insurance discount for FSD users in these two states
Tesla’s Safety Scores are used to determine premium rates for buyers of the company’s in-house insurance program, except in California, where privacy laws prohibit the use of real-time driving data to determine premiums. The company also says that its latest formula for Safety Scores were generated using over 22 billion miles of fleet data from its cars, while the company plans to continue improving the formula as more data comes in.
At this time, Tesla Insurance is available in the following 12 states, though Safety Scores aren’t available in California for the aforementioned reason:
- Arizona
- California
- Colorado
- Illinois
- Maryland
- Minnesota
- Nevada
- Ohio
- Oregon
- Texas
- Utah
- Virginia
You can see the factors that make up Tesla’s Insurance Safety Scores below or on its website here, along with the specific formula that makes up a drivers’ 0 to 100 Safety Score.
Hard Braking
Credit: Tesla
Hard braking is defined as backward acceleration, measured by your Tesla vehicle, in excess of 0.3g. This is the same as a decrease in the vehicle’s speed larger than 6.7 mph, in one second. Hard braking is introduced into the Safety Score Beta formula as the proportion of time where the vehicle experiences backward acceleration greater than 0.3g as a percentage of the proportion of time the vehicle experiences backward acceleration greater than 0.1g (2.2 mph in one second). Hard braking while on Autopilot is not factored into the Safety Score Beta formula. For vehicles with Autopilot computer 3.0 or greater, braking while the vehicle detects yellow traffic lights is also not factored into the Safety Score Beta formula. If the vehicle is unable to detect a yellow traffic light at the time of the hard braking, the event will impact your Safety Score. The percentage shown in the app is the proportion of time spent braking done with excessive force when driving and Autopilot is not engaged. The value is capped at 5.2 percent in the Safety Score Beta formula.
Aggressive Turning
Credit: Tesla
Aggressive turning is defined as left/right acceleration, measured by your Tesla vehicle, in excess of 0.4g. This is the same as an increase in the vehicle’s speed to the left/right larger than 8.9 mph, in one second. Aggressive turning is introduced into the Safety Score Beta formula as the proportion of time the vehicle experiences left or right acceleration greater than 0.4g as a percentage of the proportion of time the vehicle experiences left or right acceleration greater than 0.2g (4.5 mph in one second). Aggressive turning while on Autopilot is not factored into the Safety Score Beta formula. The percentage shown in the Tesla app is the proportion of time spent turning with excessive force when driving and Autopilot is not engaged. The value is capped at 13.2 percent in the Safety Score Beta formula.
Unsafe Following
Credit: Tesla
Your Tesla vehicle measures its own speed, the speed of the vehicle in front and the distance between the two vehicles. Based on these measurements, your vehicle calculates the number of seconds you would have to react and stop if the vehicle in front of you came to a sudden stop. This measurement is called “headway.” Unsafe following is the proportion of time where your vehicle’s headway is less than 1.0 seconds relative to the time that your vehicle’s headway is less than 3.0 seconds. Unsafe following is only measured when your vehicle is traveling at least 50 mph and is incorporated into the Safety Score Beta formula as a percentage. Unsafe following while on Autopilot is not factored into the Safety Score Beta formula. The percentage shown in the Tesla app is the percentage of unsafe following when driving and Autopilot is not engaged. The value is capped at 63.2 percent in the Safety Score Beta formula.
Excessive Speeding
Credit: Tesla
Excessive Speeding is defined as the proportion of time spent driving in excess of 85 mph or driving 20% faster than the vehicle in front of you, when that vehicle is going over 25 mph and is within 100 meters of your vehicle. This value is expressed as a percentage of total driving time and is capped at 10.0% in the Safety Score Beta formula. Speeding while on Autopilot is not factored into the Safety Score Beta formula.
Late-Night Driving
Credit: Tesla
Late-Night Driving is defined as the number of seconds you spend driving at night (11 PM – 4 AM) divided by the number of seconds you spend driving total during the day and night. Due to the variable risk level associated with driving during each late-night hour, each hour is weighed differently, and driving at each hour will affect your Safety Score differently. For example, driving at 11 PM will not affect your Safety Score as heavily as driving at 2 AM. Drive sessions that span two days will apply to the day the trip ends. Late-Night Driving includes all driving at night (11 PM – 4 AM) including any driving done on Autopilot. The value is capped at 14.2 percent in the Safety Score Beta formula.
Forced Autopilot Disengagement
Credit: Tesla
The Autopilot system disengages for the remainder of a trip after the driver has received three audio and visual warnings. These warnings occur when your Tesla vehicle has determined that the driver has not applied sufficient resistance to the steering wheel or has become inattentive. Forced Autopilot Disengagement is introduced into the Safety Score Beta formula as a 1 or 0 indicator. The value is 1 if the Autopilot system is forcibly disengaged during a trip, and 0 otherwise.
Unbuckled Driving
Credit: Tesla
Unbuckled Driving is defined as the proportion of time spent driving above 10 mph without fastening the driver’s seatbelt in a Tesla vehicle, as a percentage of time spent driving above 10 mph. The value shown in the Tesla app is the proportion of time driven at a speed over 10 mph, without buckling the driver’s seatbelt, as a percentage of time spent driving over 10 mph. The value is capped at 31.7 percent in the Safety Score Beta formula.
Tesla’s formula for Safety Score beta v2.2
Tesla takes the formula pictured below, dubbed its Predicted Collision Frequency (PCF), and converts it into the 0 to 100 version 2.2 Safety Score it assigns based on driver behavior. The 2.1 Safety Score formula can also be seen on the Tesla Insurance page, though the below formula is for the newly launched version 2.2.
Credit: Tesla
Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.
Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.
Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.
These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.
READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.
For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.
🚨 Tesla Full Self-Driving v14.3 proceeds through an Except Right Turn Stop Sign pic.twitter.com/YemRSlens7
— TESLARATI (@Teslarati) April 8, 2026
That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.
This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.
Florida Governor Ron DeSantis has sharply criticized legacy media outlets for what he describes as selective and biased reporting on vehicle accidents involving Tesla. In a recent X post, DeSantis questioned why headlines routinely spotlight the Tesla brand in crash stories, even when human error is the clear cause, while similar incidents with other automakers often receive generic treatment.
A prime example is the June 19, 2026, fatal crash in Katy, Texas. A Tesla Model 3 driven by Michael Butler struck a brick home at high speed, killing 76-year-old Martha Avila inside. Initial reports and headlines prominently featured “Tesla crash” and referenced the driver’s claim that an automated driving-assistance system was engaged.
Many outlets quickly speculated that Full Self-Driving or Autopilot were the cause of the crash, immediately blaming the suites for the accident shortly after it happened.
However, Tesla responded shortly after the accident with vehicle data that showed Butler manually overrode the system by pressing the accelerator to 100 percent, reaching 73 MPH in a residential area, more than double the speed limit. The accelerator remained floored after impact.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
The National Transportation Safety Board (NTSB) later confirmed these findings, and Butler now faces manslaughter charges. His phone searches also included queries like “Tesla FSD too timid,” suggesting he may have intervened aggressively. Despite this, many headlines continued to center Tesla’s technology rather than the driver’s actions.
DeSantis highlighted a Washington Post headline, which was labeled, “Newly released photo shows wreckage of Tesla crash that killed grandmother.”
Do legacy media outlets typically use headlines involving the make of a car in a crash or is that only for Tesla?
It would be one thing if the self-driving malfunctioned but the crash was purely human-induced.
Seems like these outlets want to associate Tesla with crashes as… pic.twitter.com/EmfyeYiuv6
— Ron DeSantis (@RonDeSantis) July 17, 2026
The subheadline noted the driver overrode assistance and floored the accelerator, yet the brand name dominated the framing. He asked whether legacy outlets typically name the make of a car in routine crashes or reserve that treatment for Tesla to push a narrative.
This pattern appears widespread. Crashes involving Ford, Chevrolet, or Toyota vehicles frequently appear as “pickup truck slams into home” or “fatal car crash kills pedestrian” without brand specifics, especially absent new technology angles.
High-profile Ford F-150 or Chevy Silverado incidents tied to large sales volumes often escape brand-callout scrutiny. In contrast, Tesla stories consistently lead with the manufacturer, amplifying perceptions of risk despite data showing strong overall safety performance:
🚨 Why do Tesla Owners get so defensive over the narrative of crashes involving Teslas? https://t.co/aX7ogtjTCR pic.twitter.com/KO4QWaLOKl
— TESLARATI (@Teslarati) June 24, 2026
Tesla’s own 2025 Impact Report indicates vehicles using FSD logged 0.19 major incidents per million miles, roughly eight times fewer than the U.S. average. Models like the Model Y also rank among the safest in IIHS and NHTSA testing for occupant protection. Critics argue disproportionate coverage ignores these statistics and driver behavior factors, such as younger or more aggressive Tesla owners in some studies.
DeSantis frames this as part of a broader political agenda against innovative American companies like Tesla. By consistently naming Tesla while downplaying others, media outlets risk eroding public trust and shaping perceptions detached from the evidence of human error in most cases.
As autonomous technology evolves across the industry, consistent and factual reporting will be essential to separate real safety concerns from narrative-driven coverage.
Tesla entered two new markets this week by advancing its presence in Latvia (Europe) and officially launching operations in Uruguay (South America), marking a rapid dual-continent expansion.
These moves underscore the company’s strategy to tap into emerging EV markets with supportive policies, renewable energy grids, and growing demand for sustainable transport.
Latvia: Strengthening the Baltic Footprint
In Latvia, Tesla has built on its earlier registration of Tesla Latvia SIA in late 2025 with recent steps toward full operations, including job postings for a service center and representation in Riga. This aligns with broader Baltic expansion following Lithuania’s model of pop-up stores and service centers.
Coming to Latvia https://t.co/XNkQQJ2O6a pic.twitter.com/yS9kpcNky1
— Tesla Europe, Middle East & Africa (@teslaeurope) July 17, 2026
EV penetration in Latvia stands at around 7 percent for BEVs in new passenger car registrations. 2025 data showed 1,602 BEVs out of about 22,500 total, or 7.1 percent, with combined plug-ins nearing 19 percent. Growth has been steady but below the European average, supported by government subsidies and infrastructure development. Tesla models like the Model 3 lead local EV registrations.
Vehicles for the Latvian market will likely be sourced from Gigafactory Berlin or Gigafactory Shanghai. Charging infrastructure is robust for the region as well, with over 400- 2,000 public points, with Tesla Superchargers in Riga, Jūrmala, and along Via Baltica routes offering up to 250 kW.
Uruguay: Third South American Country
Tesla teased its Uruguay arrival with “Estamos llegando,” or, “We are arriving,” on social media, followed by an official presentation scheduled for mid-July.
Hola Uruguay 🇺🇾
Nuestros Model 3 y Model Y están cada vez mas cerca! pic.twitter.com/FR41fsA7um
— Tesla Latinoamérica (@Tesla_LatAm) June 30, 2026
The company established Tesla Uruguay SAS, homologated Model 3 and Model Y (three versions each), and appointed local leadership. This makes Uruguay Tesla’s third official South American market after Chile and Colombia.
Uruguay boasts one of Latin America’s highest EV penetrations, with battery-electric vehicles exceeding 20 percent market share recently, driven by tax incentives, high fuel prices, and a nearly 95-100 percent renewable electricity grid. Hundreds of Teslas already operate via grey imports, but official sales bring warranties, service, and support.
Vehicles will be imported from Gigafactory Shanghai, enabling competitive pricing for Model 3 and Model Y. Charging plans include Supercharger development alongside existing infrastructure, leveraging the country’s green energy advantage for affordable operation.
Tesla Superchargers follow Model 3 and Model Y to South American country
Tesla’s Dual Continent Expansion
Tesla’s simultaneous push into Latvia and Uruguay demonstrates efficient scaling: prioritizing service and infrastructure first, then direct sales in high-potential niches. In Europe, it fills Baltic gaps; in Latin America, it counters Chinese dominance while leveraging renewables.
This dual move signals Tesla’s ambition to accelerate global EV adoption amid varying regional paces. By addressing local needs, like subsidies in Latvia or incentives and green grids in Uruguay, Tesla not only boosts volumes but advances its mission of sustainable energy.
For investors and consumers, it highlights resilience and opportunity in diverse markets, potentially paving the way for further growth in underserved regions. With strong fundamentals in both, these entries could yield long-term gains as EV transitions mature worldwide.
Elon Musk says your Tesla will start to learn your individual preferences
Ron DeSantis calls out media bias in Tesla crash coverage
