Tesla Reveals Updated FSD Safety Stats as Fleet Surpasses Eight Billion Miles Driven | Taha Abbasi

On February 19, 2026, Taha Abbasi reports that Tesla has released updated Full Self-Driving safety statistics alongside the revelation that FSD-equipped vehicles have collectively surpassed eight billion supervised miles. This dataset — the largest real-world autonomous driving collection in history — puts Tesla in a unique position to make statistically significant safety claims about its driver-assistance technology.

The updated data shows that Tesla vehicles operating with FSD Supervised engaged experience significantly fewer crashes per mile compared to the U.S. national average. According to Tesla’s internal data (compiled from fleet telemetry), vehicles with FSD active are involved in roughly one airbag-deployment crash per 7.5 million miles. The national average, according to NHTSA data, is approximately one airbag-deployment crash per 700,000 miles. That represents a roughly 10x safety improvement — though critics correctly note that FSD is used primarily in favorable driving conditions, which skews the comparison.

What makes this data release noteworthy, as Taha Abbasi explains, is the sheer volume behind it. At eight billion miles, even statistically rare events have occurred thousands of times, giving Tesla’s neural networks enough examples to learn from edge cases that smaller fleets would never encounter. A pedestrian stepping off a curb in a snowstorm while carrying an umbrella at twilight isn’t a hypothetical — it’s happened hundreds of times in Tesla’s dataset, and the AI has seen it.

The Acceleration Curve

Perhaps more telling than the total mileage is the rate of accumulation. Tesla’s FSD fleet added its most recent billion miles faster than any previous billion. This acceleration reflects three compounding factors: more vehicles on the road, higher FSD adoption rates among existing owners, and longer average engagement times as the system improves and drivers become more comfortable letting it handle complex scenarios.

The trajectory toward ten billion miles — a milestone that many analysts view as a psychological threshold for regulatory confidence in autonomous systems — is now clearly visible. At current rates, Taha Abbasi projects Tesla could cross ten billion supervised miles before September 2026, potentially providing the statistical foundation needed for regulatory approval of unsupervised operation in certain geofenced areas.

How Safety Data Gets Collected

Tesla’s safety data pipeline is one of the most sophisticated in the automotive industry. Every FSD-equipped vehicle continuously streams telemetry data to Tesla’s servers, including camera feeds during critical events, vehicle dynamics data (speed, acceleration, steering inputs), and driver behavior data (attention monitoring, intervention frequency). This creates a feedback loop where every mile driven contributes to both the aggregate safety statistics and the training data for next-generation FSD versions.

Importantly, Tesla also collects “shadow mode” data from vehicles where FSD is not actively engaged. In shadow mode, the car’s neural network processes the environment and generates predicted actions, which are then compared to what the human driver actually did. Disagreements between the AI’s prediction and the human’s action are flagged as potential learning opportunities and fed back into the training pipeline.

As Taha Abbasi has previously analyzed, this data collection methodology is what gives Tesla its fundamental advantage over simulation-first approaches. Real-world data captures the full complexity of human driving behavior — including the irrational, unpredictable, and culturally specific behaviors that simulations struggle to model accurately.

The Debate Over Self-Reported Data

Critics raise valid concerns about Tesla self-reporting its safety data without independent verification. Unlike Waymo, which publishes detailed safety reports reviewed by independent safety organizations, Tesla’s safety statistics come from Tesla itself. The company chooses which metrics to report, how to categorize incidents, and what comparisons to draw.

This transparency gap matters. As autonomous driving technology becomes a public safety issue, the industry needs standardized reporting metrics that allow apples-to-apples comparisons between different systems. Taha Abbasi has called for exactly this kind of standardization, arguing that public trust in autonomous driving depends on data that the public can independently verify.

Nevertheless, the eight billion mile milestone is real, the fleet continues to grow, and the statistical foundation for Tesla’s safety claims becomes stronger with every mile driven. Whether you trust Tesla’s specific numbers or not, the direction of the trend is clear: FSD is accumulating driving experience at a pace that no other autonomous system can match, and the safety data — however imperfect its reporting — is moving in the right direction.

Looking Forward

The question now shifts from “does FSD have enough data?” to “does the data support removing human supervision?” That’s a fundamentally different question — one that involves not just statistical confidence but regulatory judgment, legal liability frameworks, and public acceptance. Tesla has built the data foundation. The next chapter is about what regulators and society decide to do with it.

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About the Author: Taha Abbasi is a technology executive, CTO, and applied frontier tech builder. Read more on Grokpedia | YouTube: The Brown Cowboy | tahaabbasi.com