1 citations · 1 across the 6 of their papers we have counts for
6 papers
Post-Training in End-to-End Autonomous Driving
Ruining Yang, Muxing Wang, Yixiao Chen +8
End-to-end models that map multimodal inputs directly to future trajectories/maneuvers have emerged as an increasingly prominent research paradigm in autonomous driving. This class…
A Trajectory Generator for High-Density Traffic and Diverse Agent-Interaction Scenarios
Ruining Yang, Yi Xu, Yixiao Chen +2
Accurate trajectory prediction is fundamental to autonomous driving, as it underpins safe motion planning and collision avoidance in complex environments. However, existing benchma…
Platoon-Centric Green Light Optimal Speed Advisory Using Safe Reinforcement Learning
Ruining Yang, Jingyuan Zhou, Qiqing Wang +2
With recent advancements in Connected Autonomous Vehicles (CAVs), Green Light Optimal Speed Advisory (GLOSA) emerges as a promising eco-driving strategy to reduce the number of sto…
Trajectory Prediction Meets Large Language Models: A Survey
Yi Xu, Ruining Yang, Yitian Zhang +5
Recent advances in large language models (LLMs) have sparked growing interest in integrating language-driven techniques into trajectory prediction. By leveraging their semantic and…
Den-TP: A Density-Balanced Data Curation and Evaluation Framework for Trajectory Prediction
Ruining Yang, Yi Xu, Yun Fu +1
Trajectory prediction in autonomous driving has traditionally been studied from a model-centric perspective. However, existing datasets exhibit a strong long-tail distribution in s…
PLoc: A New Evaluation Criterion Based on Physical Location for Autonomous Driving Datasets
Ruining Yang, Yuqi Peng
Autonomous driving has garnered significant attention as a key research area within artificial intelligence. In the context of autonomous driving scenarios, the varying physical lo…