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Tesla driver faces manslaughter charges over Texas crash that killed a woman inside her home

Chimera readability score 76 out of 100, Expert reading level.

The man whose Tesla struck and killed a woman inside her Texas home last month is now facing manslaughter charges, as reported earlier by The Wall Street Journal and local news outlet KHOU 11. 44-year-old Michael Butler was arrested on Wednesday and claimed to have been driving his Model 3 using Tesla’s Full-Self Driving (FSD) system at the time of the crash, according to an arrest affidavit.
Tesla driver faces manslaughter charges over Texas crash that killed a woman inside her home
Police said Google searches showed Butler’s recent frustration with ‘timid’ FSD in his Tesla.
Police said Google searches showed Butler’s recent frustration with ‘timid’ FSD in his Tesla.
The court document includes the officer saying that data extraction from Butler’s phone found several FSD-related Google searches from May 2026: “Tesla fsd not aggressive enough 2026 model,” “tesla fsdnot [sic] aggressive enough 2026,” “tesla fsdnot [sic] aggressive enough,” “FSD is not aggressive enough for city driving,” “tesla fsdnot [sic] aggressive enough,” and “tesla fsd too timid.”
On June 19th, 76-year-old Martha Avila was killed after Butler’s vehicle plowed through her home in a residential neighborhood in Katy, Texas. Tesla AI head Ashok Elluswamy responded shortly after in a tweet, saying the driver “manually overrode self-driving by pressing the accelerator all the way to 100%.”
Avila’s family has filed a wrongful death lawsuit against Tesla and Butler, while both the National Highway Traffic Safety Administration and the National Transportation Safety Board have opened investigations into the crash.
The affidavit says Butler told paramedics that “the car was on ‘autopilot,’” adding that “he remembers changing the music… (and) looked at the navigation screen” before the fatal collision while making deliveries for DoorDash. He also told hospital providers that he “remembers putting the car in self driving mode” and that he “passed out,” according to the affidavit. An evaluation from the hospital didn’t find alcohol or drugs in Butler’s system, the affidavit says
After reviewing video from Butler’s Model 3, along with data from the vehicle’s “black box,” officials said they found that the “accelerator pedal was pressed, overriding FSD’s speed control:”
On the video, I saw BUTLER’s Tesla continue to increase in speed, and saw the amount of pressure being applied to the accelerator pedal also increase in speed. In about six (6) seconds, the accelerator pedal was pressed all the way down to 100%, “pedal to the metal,” and the vehicle reached a speed of 73 miles per hour, more than double the speed limit on that residential street. The Tesla continued straight towards the middle of the cul-de-sac, struck the curb of the complainant’s driveway, and went airborne towards the front of the home… I noted that the brake pedal was never pressed in the final minute before the crash.”
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Sentinel — Human

Confidence

The text exhibits high coherence and strong sourcing, strongly suggesting it is a human-written piece synthesizing multiple legal and physical evidence points from official reports.

Signals Detected
low severity: Sentence length variance is natural; language flows like journalistic reporting rather than uniform LLM rhythm.
low severity: Text maintains a clear narrative flow connecting personal facts, official findings (video/black box), and legal actions without excessive hedging or forced balance.
low severity: Specific details regarding the incident (dates, names, exact quotes from affidavits) are anchored to specific judicial or official sources (e.g., court documents, police statements).
low severity: The core evidence presented (video review findings, affidavit details) points toward verifiable external documentation, suggesting a human synthesis of source material rather than pure fabrication.
Human Indicators
Specific references to court documents, official investigations (NHTSA, NTSB), and direct video/black box data indicate grounding in external, verifiable evidence. The tone is investigative and fact-based, typical of journalistic reporting.
The use of specific, non-standardized details about the FSD frustration searches provides an idiosyncratic flavor that suggests human curation rather than generic LLM generation.