Simon Janssen

The work proposes a dual-process-inspired hybrid framework in which a TransFuser++ neural planner generates human-like trajectories in routine driving while a meta-cognitive component, using risk fields shaped by knowledge-graph reasoning, decides when to switch to a model predictive control planner; tested in CARLA on out-of-distribution scenarios of vehicles (including an ambulance) running a red light, it reduced vehicle-to-vehicle collisions from 48 to 5 out of 160 simulations, an 89% reduction.

The work proposes a dual-process-inspired hybrid framework in which a TransFuser++ neural planner generates human-like trajectories in routine driving while a meta-cognitive component, using risk fields shaped by knowledge-graph reasoning, decides when to switch to a model predictive control planner; tested in CARLA on out-of-distribution scenarios of vehicles (including an ambulance) running a red light, it reduced vehicle-to-vehicle collisions from 48 to 5 out of 160 simulations, an 89% reduction.