Which brings us back to the confusion between cans and pedestrians. When an autonomous car scans a person with its forward-facing radar, they show the same reflectivity as a soda can, explains Sven Beiker, executive director of the Center for Automotive Research at Stanford University. “That tells you that radar is not the best instrument to detect people. The laser or especially camera are more suited to do that.”

Just an illusion

The hard part is getting a robot to intelligently identify what it has detected. We take for granted what goes into creating our own view of the road. We tend to think of the world falling onto retinas like the picture through a camera lens, but sight is much more complicated. “The whole visual system shreds images, breaks them up into maps of colour, maps of motion, and so on, and somehow then manages to reintegrate that,” explains Peter McOwan, a professor of computer science at Queen Mary, University of London. How the brain performs this trick is still a mystery, but it’s one he’s trying to replicate in robot brains by studying what happens when we have glitches in our own vision.

There are some images that our brains consistently put together incorrectly, and these are what we call optical illusions. McOwan is interested in optical illusions because if his mathematical models of vision can predict new ones, it's a useful indicator that the model is reflecting human vision accurately. “Optical illusions are intrinsically fascinating magic tricks from nature but at the same time they are also a way to test how good your model is,” he says.

Most robots, for example, would not be fooled by the Adelson checkerboard illusion where we think two identical grey squares are different shades: