Self-Driving Car Sensors

There are vision systems on the side. The car primarily relies on its vision system, like humans. The radar is a check, not the primary.

How do humans drive without these sensors?

Radar and lidar may be needed but this is not a good example of it. I am watching this video on youtube recorded with a camera. I can clearly see the lanes in this video and I can clearly see the oncoming traffic. The car should not have crossed over and it should be able to detect the large light approaching in the other lane. This is a completely failure of the AI that radar and lidar would fail to solve.

I don't get it, the system relies on two kinds of sensors ? radars for rear-ends and optical cameras for broader decision making ? so that location confused the cameras and that was it ? the car has no ability to understand its surrounding outside crude parsing of the visual field (trained ML I suppose)...that's quite fucked up.

Are these cars using only visual data? I thought many used some kind of LIDAR as well, where that might cut through visibility issues depending on the wavelength used.

My thought: LIDARs and other kind of sensors are much better than human eyes. I'd expect the current self-driving cars to have already better sensory resolution than human drivers.

Sensors and cameras can't really see something, but the eye and the brain of a human can guess, all senses are at 100% (humans are tired after driving in such conditions). Making an IA which can have the same performance/evaluation must be really tricky

More sensors doesn't mean waymo doesn't rely on AI and computer vision.

The problem is not the AI (driving is relatively simple), but the sensors. Cameras are bad vs. our eyes.

Cool video. I guess while self driving cars may have inferior analysis to humans for a while they may outperform through better sensors like the radar here.