Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility
TraCS is a neuro-symbolic framework that improves motion prediction by adding interpretable, probabilistic first-order logic to existing neural models. It uses an agentic code generation pipeline to translate natural language traffic rules into logical constraints, which then shape the backbone's predictions. This approach consistently outperforms purely neural predictors by providing context-aware compliance reasoning.