In a tightly controlled parking-lot experiment, GPT-6 Astra drove a real Toyota Corolla through a cone course and finished on its second attempt. Grok 4.6 did not crash immediately in the literal sense: its best reported run covered 11% of the route. The demonstration showed that AI models can issue driving commands through an experimental setup; it did not show that a chatbot is ready to drive on public roads.
What happened in the test?
DrivingBench gave four general-purpose AI models control of a 2022 Toyota Corolla fitted with a Comma Four aftermarket device and modified openpilot. A custom harness let each model inspect camera images and vehicle state, send steering and speed commands for a chosen duration, or stop the car. New commands replaced active ones rather than waiting in a queue.
The experiment took place on a 134.7-meter parking-lot course marked by cones. The reported speed cap was 3.5 meters per second, about 8 mph. Additional safety limits were in place, and a human operator sat ready to brake. The models ran in their respective agent environments at medium reasoning effort. Each could make up to three attempts in one continuing conversation; after a failure, the operator asked it to reflect on what went wrong. The detailed account was published by Auto Connected Car News on October 5, 2026.
How did the models perform?
| Model | Reported course progress by attempt | Completed? | Other reported detail |
|---|---|---|---|
| GPT-6 Astra | About 49% on the first attempt; completed on the second | Yes, on attempt two | Successful run took 5 minutes 22 seconds |
| Claude Fable 5.1 | 9%, 10%, then 45% | No | Progress improved over the three attempts |
| Grok 4.6 | 8%, 11%, then 10% | No | Best reported progress was 11% |
| GPT-5.6 Sol | 6% on each of three attempts | No | Progress did not change across attempts |
The percentages and times are results from this reported test session, not general performance or safety rates. Because each model’s retries continued in the same conversation, the attempts were not independent. The account describes only one evaluation per model, so the scorecard is too small and context-specific to establish a general ranking.
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Why was the successful run still limited?
Astra’s completion was notably cautious and slow: the report says the car averaged below 1 meter per second and never exceeded 0.8 meters per second. It used full steering lock on 20 of its 24 commands. A slow, short-command strategy may help explain how it negotiated this particular course, but it is not evidence of competent driving in ordinary traffic.
The reported problems reveal how much the task depended on interpreting a constrained visual scene and issuing commands through a custom interface:
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- Models misread which side of a diagonal cone boundary marked the lane.
- They misjudged the car’s width based on camera views.
- Some deliberation took place while the car remained in motion, creating delays before the next command.
The report says Astra switched to shorter, slower movements after reflecting on its first run. Claude also made more progress by its third attempt but did not finish. Those observations describe behavior in this setup; they do not show how the models would perform with different routes, vehicles, sensors, or traffic.
Does this mean ChatGPT can drive on public roads?
No. DrivingBench was a low-speed, cone-marked parking-lot demonstration with an operator ready to intervene. It was not a public-road evaluation, a comparison against a validated autonomous-driving system, or proof that a chatbot can safely replace one.
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The test’s limits matter when interpreting the result: the course was constrained; cameras had blind spots near the car and along its sides and rear; steering was subject to limits imposed by the Comma setup; and the report notes a flaw in its example for explaining steering. The small number of evaluations and shared conversation context further restrict what can be concluded.
The same news account also reported that NHTSA opened preliminary evaluation PE26007 on September 21 concerning Comma Three, Comma 3X, Comma Four, and openpilot after reports of crashes involving equipped vehicles. The account cautions that opening a preliminary evaluation does not establish that the hardware or software caused those crashes. Those reported highway incidents are separate from DrivingBench’s controlled, low-speed course. See the account’s discussion of the benchmark and regulatory context.
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What the headline leaves out
“Grok crashed immediately” compresses a more nuanced scorecard: Grok’s three reported attempts reached 8%, 11%, and 10% of the route. The test account does not support treating the headline as a literal description of an immediate crash. Likewise, saying ChatGPT “can drive a car” needs qualification: one model completed one specific course on its second try under safeguards, at very low speed. The result is a proof-of-capability demonstration, not evidence of road readiness.
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