7 papers
Aligning Microscopic Vehicle and Macroscopic Traffic Statistics: Reconstructing Driving Behavior from Partial Data
Zhihao Zhang, Keith Redmill, Chengyang Peng +1
A driving algorithm that aligns with good human driving practices, or at the very least collaborates effectively with human drivers, is crucial for developing safe and efficient au…
SignRAG: A Retrieval-Augmented System for Scalable Zero-Shot Road Sign Recognition
Minghao Zhu, Zhihao Zhang, Anmol Sidhu +1
Automated road sign recognition is a critical task for intelligent transportation systems, but traditional deep learning methods struggle with the sheer number of sign classes and…
An Uncertainty-Weighted Decision Transformer for Navigation in Dense, Complex Driving Scenarios
Zhihao Zhang, Chengyang Peng, Minghao Zhu +2
Autonomous driving in dense, dynamic environments requires decision-making systems that can exploit both spatial structure and long-horizon temporal dependencies while remaining ro…
Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
Zhihao Zhang, Chengyang Peng, Ekim Yurtsever +1
Automated vehicle control using reinforcement learning (RL) has attracted significant attention due to its potential to learn driving policies through environment interaction. Howe…
Reinforcement Learning with Data Bootstrapping for Dynamic Subgoal Pursuit in Humanoid Robot Navigation
Chengyang Peng, Zhihao Zhang, Shiting Gong +3
Safe and real-time navigation is fundamental for humanoid robot applications. However, existing bipedal robot navigation frameworks often struggle to balance computational efficien…
Lightweight Authenticated Task Offloading in 6G-Cloud Vehicular Twin Networks
Sarah Al-Shareeda, Fusun Ozguner, Keith Redmill +2
Task offloading management in 6G vehicular networks is crucial for maintaining network efficiency, particularly as vehicles generate substantial data. Integrating secure communicat…