Say for example, the designers never trained the car's system to recognize someone on a skateboard as an obstacle.
Obviously a lidar based system would spot the skater, but a camera+ai system depends on being trained to identify each type of obstacle as an obstacle and avoid it.
Do you really need to train your AI to spot people on skateboards vs rollerskates vs rollerblades vs heelies vs sliding on ice vs traveling on a travelator vs standing on a moving vehicle vs ...?
OK, being able to recognise the differences and act accordingly might be useful but the principle of "person getting closer to vehicle" should hold sway for most situations?!?
I think the big thing is that not all of these 'persons' move in the same way. A person in the exact same location could both be a 'hazard' and 'not a hazard' based solely on their velocity, and their ability to change direction quickly (and are they chasing after something which isn't a hazard, but which is intercepting your driving path). They don't just have to identify the person, they have to be capable of forecasting that person's movement.
IOW, someone walking and someone on a skateboard are different risks, because the skateboard could move into your path of travel before your pass them, whereas someone walking would not.
>human moving towards you at X speed
Lidar systems will work this way. Camera+AI not necessarily, it will still need a way to sense relative speed otherwise you are banking on an AI to identify an obstacle in an image.
Don't assume that self-driving software is designed with even a minimal level of competence.
Footnote: there have been many articles about this incident posted to HN. Here's one: https://news.ycombinator.com/item?id=19333239