3 papers
cs.MA2026
Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO
Shuyang Li, Ruimin Ke
The integration of Large Language Models (LLMs) with microscopic traffic simulation offers a promising path toward autonomous urban planning and intelligent transportation analysis…
quant-ph2026
Impact-Driven Quantum Decomposition for Traffic Zone Partitioning: A Hybrid Gate-Model Framework
Ruimin Ke, Talha Azfar, Kaicong Huang +1
Partitioning transportation networks into balanced and spatially coherent traffic zones is a fundamental yet computationally challenging task in intelligent transportation systems.…
cs.HC2024
ChatSUMO: Large Language Model for Automating Traffic Scenario Generation in Simulation of Urban MObility
Shuyang Li, Talha Azfar, Ruimin Ke
Large Language Models (LLMs), capable of handling multi-modal input and outputs such as text, voice, images, and video, are transforming the way we process information. Beyond just…