3 papers
cs.LG2025
Theory Foundation of Physics-Enhanced Residual Learning
Shixiao Liang, Wang Chen, Keke Long +3
Intensive studies have been conducted in recent years to integrate neural networks with physics models to balance model accuracy and interpretability. One recently proposed approac…
cs.RO2025
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
Junwei You, Haotian Shi, Zhuoyu Jiang +6
Vehicle-to-everything (V2X) cooperation has emerged as a promising paradigm to overcome the perception limitations of classical autonomous driving by leveraging information from bo…
cs.RO2024
Online Adaptive Platoon Control for Connected and Automated Vehicles via Physics Enhanced Residual Learning
Peng Zhang, Heye Huang, Hang Zhou +3
This paper introduces a physics enhanced residual learning (PERL) framework for connected and automated vehicle (CAV) platoon control, addressing the dynamics and unpredictability…