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$243M Verdict Against Tesla After Fatal Autopilot Crash

Case: Benavides, et al. v. Tesla, Inc., No. 1:21-cv-21940 (S.D. Fla.)

In 2019, a Tesla Model S equipped with its Autopilot driver-assistance system crashed at a T-intersection in Key Largo, Florida. The driver, George McGee, reportedly dropped his phone onto the floorboard, looked down to pick it up, failed to stop at a stop sign and red light, and struck a parked Chevrolet Tahoe beside which a couple, Naibel Benavides Leon and Dillon Angulo, were standing. Leon was killed; Angulo was seriously injured.

At trial in 2025, a Miami federal jury found Tesla 33% responsible for the crash. Hence, Tesla was ordered to pay approximately $42.6 million in compensatory damages (part of a total of $129 million) and $200 million in punitive damages, for a combined verdict of $243 million. Tesla plans to appeal, arguing that the driver’s negligence was the main cause and that the verdict threatens innovation.

Evidence played a big role: Tesla initially claimed it did not have a “collision snapshot” (data from the Autopilot unit showing what the vehicle saw just prior to the crash), but it later emerged that the data had been recorded and stored, though allegedly mishandled.

Tesla has moved for a judgment as a matter of law or, alternatively, for a new trial or to amend the judgment.

Why It Matters
  • Shifts in liability expectations: Automakers may be seen as partially responsible not only for what drivers do, but for how their driver-assist/autonomous systems are designed, marketed, and implemented—even when the driver is negligent.
  • Greater cost and risk from punitive damages: The size of the award, especially the punitive portion, signals that juries may penalize companies severely for misconduct, misrepresentation, or mishandling of safety-critical data.
  • Evidence, transparency, and data handling matter: How companies collect, store, and disclose data from driver-assist systems can be decisive in litigation. Missing or poorly preserved data can hurt a defense.

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