Ask HN: How do they write test coverage for driverless cars?
How they write test suites for driverless cars? For example, it seems that you'd need to run through the same tests multiple times in different weather conditions, with broken signage, with signage and traffic rules for different countries, and so forth.
6 comments
They use all the data they collect from the real world to run endless simulations. There was something about this in the January 2016 status report from Google.
"All together, we drive more than 3 million miles in simulation every day."
https://www.google.com/selfdrivingcar/reports/
"All together, we drive more than 3 million miles in simulation every day."
https://www.google.com/selfdrivingcar/reports/
Lots of good stuff there, thanks. But not finding anything addressing formal, repeatable test suites.
I don't think they can do formal checking in such cases. The best they can do is to run a number of tests on a number of scenarios.
However, this is a scenario with large input sets and infinite test cases, I don't think they can ever formally check every possibility.
However, this is a scenario with large input sets and infinite test cases, I don't think they can ever formally check every possibility.
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I would guess that there are three major components to the cars - the data collection (sensors, cameras, GPS, etc), the driving mechanism (throttle, brakes, wheel), and the logic unit ("should I accelerate into this minivan?")
I would assume they run the logic unit through simulations independently of the other systems in many instances.
I would assume they run the logic unit through simulations independently of the other systems in many instances.
One can assume those things, but should one? So many problems come to mind. For example, you can overtrain neural nets. How do they avoid that problem? Do they have tests that do so? Or driving on the other side of the road, as in Britain vs. United States.
Hire someone with lots of experience writing drivers!