The slideshow 10 astonishing technologies that power google’s self-driving cars documents some of the technologies used in Google's self-driving car. It mentions a radar.

Why does Google use radar? Doesn't LIDAR do everything radar can do? In particular, are there technical advantages with radar regarding object detection and tracking?

To clarify the relationship with AI: how do radar sensors contribute to self-driving algorithms in ways that LIDAR sensors do not?

The premise is AI algorithms are influenced by inputs, which are governed by sensors. For instance, if self-driving cars relied solely on cameras, this constraint would alter their AI algorithms and performance.

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    $\begingroup$ I think it comes down to cost, mostly, see: eetimes.com/author.asp?section_id=36&doc_id=1330069. Lidar is used to produce very detailed topography maps from airborne vehicles, but is more expensive. Radar is cheap and well understood, and signal attenuation is not so important over the distances the a self-driving car needs to sense. $\endgroup$ – John Powell Oct 20 '16 at 13:57

LIDARs, especially cheap LIDARs, have problems with reflective surfaces (like metallic paint on cars), strong lights like car headlights, weather(rain, snow, hail, fog), and have a considerably shorter range than comparable in price radars. Of course, they have much better precision, so some hardware stacks for cars are using both.


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