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In fact, Google has the most expensive set of sensors on any self-driving prototype out there, AFAIK. They spend about $150k per car on sensors. But almost all the technology they've shown is about detecting people, dogs, other obstacles, on a largely unchanging setting. As of late 2014[0], Google engineers admitted the mapping required for their cars to work wasn't feasible at a nationwide scale, and that if they didn't know to look for say, a stoplight, on their maps, they'd run right through it. (Looking for arbitrary red lights is probably a hard problem too.) That's two years ago, yes, but they've announced nothing, technologically, in this field in this time (please comment if you have an additional source relating to the mapping of the roadway for a Google car), despite tons of PR about the number of miles they've driven or what cities they were driving in, with the same technology they've already had. Also bear in mind, almost all of Google's senior talent in self-driving cars has left Google X. So if they were having trouble with this problem in 2014, their newer, less experienced people now, probably are having more difficulty in 2016. [0]http://www.slate.com/articles/technology/technology/2014/10/... |
[1] https://en.wikipedia.org/wiki/Traffic_sign_recognition [2] http://blog.caranddriver.com/how-high-definition-maps-are-pl...