Our safety research team is interested in this topic, too! In a previous study, they've tried to model it:
> Building on that, the Collision Avoidance Benchmarking paper presents a novel methodology to evaluate how well autonomous driving systems avoid crashes. The study, which to our knowledge is the first of its kind, introduces a reference model that represents an ideal human state for driving—the response time and evasive action of a human driver that is non-impaired, with eyes always on the conflict (NIEON). Put simply, unlike an average human driver, NIEON is always attentive and doesn’t get distracted or fatigued¹. The data showed that the Waymo Driver outperformed the NIEON human driver model by avoiding more collisions and mitigating serious injury risk in simulated fatal crash scenarios.
AIUI (I'm not on that team), a major challenge is getting good baseline data. Collision reports may not (reliably) capture that kind of data, and it's clearly subjective or often self-reported outside of cases like DUI charges.
> Building on that, the Collision Avoidance Benchmarking paper presents a novel methodology to evaluate how well autonomous driving systems avoid crashes. The study, which to our knowledge is the first of its kind, introduces a reference model that represents an ideal human state for driving—the response time and evasive action of a human driver that is non-impaired, with eyes always on the conflict (NIEON). Put simply, unlike an average human driver, NIEON is always attentive and doesn’t get distracted or fatigued¹. The data showed that the Waymo Driver outperformed the NIEON human driver model by avoiding more collisions and mitigating serious injury risk in simulated fatal crash scenarios.
(From https://waymo.com/blog/2022/09/benchmarking-av-safety)
AIUI (I'm not on that team), a major challenge is getting good baseline data. Collision reports may not (reliably) capture that kind of data, and it's clearly subjective or often self-reported outside of cases like DUI charges.