2 citations · 2 across the 5 of their papers we have counts for
5 papers
SimTIO: A Simulation-Grounded Multi-Agent LLM Framework for Compositional Traffic Intervention Optimization
Shuyang Li, Ruimin Ke
Traffic analysts must translate diagnosed bottlenecks into executable interventions without allowing local improvements to degrade network-wide performance. This study presents Sim…
Risk-Adaptive Edge--Cloud Visual Reasoning for Communication-Efficient Autonomous Driving
Meng Ma, Shuyang Li, Naigang Wang +1
Cloud-hosted vision-language models (VLMs) offer greater contextual reasoning capabilities than smaller onboard models, but frequent visual uploads increase communication overhead…
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…
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.…
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…