Introducing Waymo’s New Reference Model for Human Collision Avoidance Today, we are proud to share that Nature Communications has published our joint research with TU Delft, advancing a breakthrough active inference framework to model human crash-avoidance behavior. This work marks a significant leap in enhanced capabilities and increased realism for our established methodology, providing a careful, competent human driver benchmark for collision avoidance. At Waymo, we call this model ReD (Reference Driver) and use it to assess the Waymo Driver’s ability to avoid crashes. ReD represents the latest advancement in Waymo’s safety research, which includes a dozen published papers on behavioral reference models. It is built upon the same predictive processing framework that powers our established NIEON (Non-Impaired driver with Eyes ON the conflict) model and an earlier active inference model of adaptive human driver behavior, ensuring continuity in our approach. The central idea underlying these models is that human driving behavior can be generally understood as the minimization of surprise. While NIEON focuses on modeling when a human might react to a threat, ReD expands upon these capabilities to model the full closed-loop cognitive process. ReD simulates how a careful and competent human driver updates their beliefs as a situation evolves, manages uncertainty about other road users' intentions, and selects the evasive maneuver, whether that is braking, swerving, or a combination of both. For decades, the automotive industry has used physical and virtual crash dummies to evaluate a car’s safety features, including its hardware and structural integrity. ReD evolves this concept, serving as a behavioral benchmark for autonomous driving systems able to realistically represent reasonable expectations on how a careful and competent human driver responds to traffic conflicts. The cognitive workflow of the ReD model, illustrating the closed-loop process of belief updating, surprise accumulation, and optimal policy selection As