5 papers
BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving
George Ling, Lijin Yang, Hao Yang +1
We present BLUE, a minimal method for better language use in vision-language-action (VLA) models for autonomous driving (AD). Through extensive analysis, we reveal that language ma…
Generative AI for Autonomous Driving: Frontiers and Opportunities
Yuping Wang, Shuo Xing, Cui Can +44
Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation,…
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…
MetaFollower: Adaptable Personalized Autonomous Car Following
Xianda Chen, Kehua Chen, Meixin Zhu +5
Car-following (CF) modeling, a fundamental component in microscopic traffic simulation, has attracted increasing interest of researchers in the past decades. In this study, we prop…