Jia-Xin Tan

A spatio-temporal context-aware LLM-centric framework for autonomous vehicle scheduling

Experimental results show that the proposed P-LLM framework outperforms traditional scheduling methods and existing reinforcement learning baselines, and maintains stable and consistent performance across different real-world scenarios, time periods, fleet sizes, and order volumes.