You're reading constraints into the experiment that don't appear to exist. My take is that after 15 minutes of driving the algorithm could correctly identify which driver was behind the wheel. That means: I get in, start driving, and within 15 minutes or so, the system analyzing the car's internal network will, with 90% specificity, say, "The driver was 'rosser."

I don't see where you're coming up with only 15 minutes total driving. That isn't implied anywhere in The Fine Article. But even leaving that detail aside, it would actually be more impressive than the reported finding if they were correctly identifying people that well after only 15 minutes total!

It's (b).

If each driver is run in twenty 15-minute (or longer) trials, you have 300 total data points to analyze. If the car was correct in its fingerprinting 270 times, then it was correct 90% of the time.

Yes, but the only way you get a number not divisible by 15 is if, for some number of given drivers, it must have been correct for some trips but incorrect for others. I would not consider those drivers to be "successfully identified". Remember, the goal of this is to isolate individual drivers.

> it must have been correct for some trips but incorrect for others.

No, it could have been inconclusive for the other 10% of the trips, simply stating, "Insufficient data for meaningful answer". So 90% of the time it said, "Oh, this must be DrScump" and the other 10% of the time it said, "I don't know who this is yet, let me keep analyzing the braking patterns"

EDIT: Which is different than the way I stated it in my initial comment. Your reply helped me realize that.

But this is a binary problem (they did or did not ID the driver); "inconclusive" = did not.

Yes, 10% of the time. The other 90% it did. So.. 90%. Not being snarky or passive aggressive, I just don't understand the issue you're having with that statistic.