Evaluation of "As-Intended" Vehicle Dynamics using the Active Inference Framework

Abstract

We constructed a computational model of the driver's brain for steering tasks using the active inference framework, grounded in the free energy principle - a theory from computational neuroscience. This model enables quantitative estimation of how accurately the brain learns vehicle dynamics and performs appropriate steering, using a measure called variational free energy. Through driving simulator experiments, we observed strong correlations between variational free energy and both expert drivers' subjective "as-intended" scores and general participants' objective control performance. These results suggest that variational free energy provides a promising quantitative metric for evaluating whether a vehicle behaves "as-intended."