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It is a ROC curve/precision-recall issue basically. Radar has a terrible lateral and even worse to non-existing elevation measurement. Potholes, man holes, Coke cans and ground clutter look all alike and can in fact be detected as "having the negative relative velocity as my car's own velocity". You want to stop for only very few of all those stationary objects, otherwise you won't drive at all. The problem is you can't classify the relevant ones with radar. Which is why the camera helps, but obviously (for false positive suppression and a high availability of the autopilot) only if it positively classifies a car's rear.


The military does it with SAR (synthetic aperture radar). Is something like that feasible for self-driving cars?


Consider price point implications.


Well, if SDVs take off as advocates espouse, the volume (plus Moore's Law) will make costs drop.


Volume maybe, but Moore's Law definitely not.


No, since you need movement to create the along-track aperture, you would have already moved through the aperture, running over what you are trying to detect.


This rather sounds like radar is the wrong choice, does it not?




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