OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Control
Researchers introduce OracleTSC, an LLM-based traffic signal control system that combines reward hurdle mechanisms and uncertainty regularization to stabilize reinforcement learning training. The approach achieves 75% reduction in travel time while maintaining interpretability through natural language explanations, with strong cross-intersection generalization capabilities.