PHLEX: Physically Layered Explanation for Counterfactual Motion Planning

Predicted trajectories describe where an agent may move, but provide limited insight into the physical mechanisms behind that motion and are difficult to systematically vary for counterfactual reasoning. We introduce PHLEX (PHysically Layered EXplanation), a predictor-agnostic framework that maps predicted motion into a structured physical mechanism representation. PHLEX progressively explains each trajectory through kinematic models, longitudinal and lateral control laws, and scene references. Together, these layers form a structured physical explanation of how the predicted motion is generated and grounded in the scene. These explanations can be executed and varied to generate physically grounded counterfactual futures, which are further used to guide ego planning. This connects the flexibility of learned trajectory prediction with explicit physical interpretation and controllable what-if reasoning. Experiments across multiple predictors and datasets show that PHLEX improves physical feasibility and planning safety while preserving trajectory accuracy.