First, I don’t think that’s the right comparison. You need to compare them to taxis.

It’s not just that, you generally have a significant distribution shift when comparing the self-drivers/driving assistants to normal humans. This is because people only use self-driving in situations where it has a chance of working, which is especially true with stuff like tesla’s self-driving where ultimately people are not even going to start the autopilot when it gets tricky (nevermind intervening dynamically: they won’t start it in the first place!)

For instance, one of the most common confounding factors is the ratio of highway driving vs non-highway driving: Highways are inherently less accident prone since you don’t have to deal with intersections, oncoming traffic, people merging in from every random house, or children chasing a ball into the street. Self-drivers tend to report a lot more highway traffic than ordinary drivers, due to how the availability of technology dictates where you end up measuring. You can correct for that by e.g. explicitly computing the likelihood p(accident|highway) and use a common p(highway) derived from the entire population of car traffic.