108 citations · 184 across the 12 of their papers we have counts for
5 papers · 1 filter
Automating Traffic Model Enhancement with AI Research Agent
Xusen Guo, Xinxi Yang, Mingxing Peng +3
Developing efficient traffic models is crucial for optimizing modern transportation systems. However, current modeling approaches remain labor-intensive and prone to human errors d…
Diffusion Models for Intelligent Transportation Systems: A Survey
Mingxing Peng, Kehua Chen, Xusen Guo +4
Intelligent Transportation Systems (ITS) are vital in modern traffic management and optimization, significantly enhancing traffic efficiency and safety. Recently, diffusion models…
GenFollower: Enhancing Car-Following Prediction with Large Language Models
Xianda Chen, Mingxing Peng, PakHin Tiu +4
Accurate modeling of car-following behaviors is essential for various applications in traffic management and autonomous driving systems. However, current approaches often suffer fr…
Towards Explainable Traffic Flow Prediction with Large Language Models
Xusen Guo, Qiming Zhang, Junyue Jiang +4
Traffic forecasting is crucial for intelligent transportation systems. It has experienced significant advancements thanks to the power of deep learning in capturing latent patterns…
LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models
Mingxing Peng, Xusen Guo, Xianda Chen +2
To ensure safe driving in dynamic environments, autonomous vehicles should possess the capability to accurately predict lane change intentions of surrounding vehicles in advance an…