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This comment made me wonder how they train the car for different sets of traffic rules. Some of this goes beyond formal rules. On most US highways you are techn

This comment made me wonder how they train the car for different sets of traffic rules. Some of this goes beyond formal rules. On most US highways you are technically supposed to overtake on the right, but it's totally common. In contrast in much of Europe this is actually enforced and the convention is that you only leave the rightmost lane while overtaking. Do you do 100% of training on data from the same region? Are there low-level skills that all translate and don't bring the risk of training contradictory expectations? Can you just annotate training data with the rule set/location that applies?

D13Fd 4y ago
> On most US highways you are technically supposed to overtake on the right You mean the left?
- 9dev 4y ago
  I think they meant „aren’t technically supposed to“, that makes more sense
- ajmurmann 4y ago
  Yeah, sorry, I omitted the "not". In practice both seem believable looking at traffic here.
Barrin92 4y ago
when it comes to decision-making there is a lot of hardcoded rules in these systems. They don't learn the speed limits or to stop at red lights. The learning is all in the perception and object recognition but a lot of the behavior is just explicit rules.