5 papers · 1 filter
Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers
Rui Yang, Lei Zheng, Shuzhi Sam Ge +1
Autonomous vehicles must navigate dynamically uncertain environments while balancing safety and efficiency. This challenge is exacerbated by unpredictable human-driven vehicle (HV)…
Occlusion-Aware Consistent Model Predictive Control for Robot Navigation in Occluded Obstacle-Dense Environments
Minzhe Zheng, Lei Zheng, Lei Zhu +1
Ensuring safety and motion consistency for robot navigation in occluded, obstacle-dense environments is a critical challenge. In this context, this study presents an occlusion-awar…
Bilevel Multi-Armed Bandit-Based Hierarchical Reinforcement Learning for Interaction-Aware Self-Driving at Unsignalized Intersections
Zengqi Peng, Yubin Wang, Lei Zheng +1
In this work, we present BiM-ACPPO, a bilevel multi-armed bandit-based hierarchical reinforcement learning framework for interaction-aware decision-making and planning at unsignali…
Occlusion-Aware Contingency Safety-Critical Planning for Autonomous Driving
Lei Zheng, Rui Yang, Minzhe Zheng +3
Ensuring safe driving while maintaining travel efficiency for autonomous vehicles in dynamic and occluded environments is a critical challenge. This paper proposes an occlusion-awa…
LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models
Zengqi Peng, Yubin Wang, Xu Han +2
Recent advancements in reinforcement learning (RL) demonstrate the significant potential in autonomous driving. Despite this promise, challenges such as the manual design of reward…