activity
20232026
most citedTraffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory control

30 citations · 49 across the 13 of their papers we have counts for

collaborators
Showing cs.ROShow all

7 papers · 1 filter

cs.RO2026

Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving

Zilin Huang, Zhengyang Wan, Zihao Sheng +3

Vision-language-model (VLM)-guided reinforcement learning (RL) has recently attracted significant attention for it, replacing brittle hand-crafted rewards with semantically grounde…

cs.RO2026

DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving

Zilin Huang, Zihao Sheng, Zhengyang Wan +4

Traditional reinforcement learning (RL) methods rely on manually engineered rewards or sparse collision signals, which fail to capture the rich contextual understanding required fo…

cs.RO2025

Sky-Drive: A Distributed Multi-Agent Simulation Platform for Human-AI Collaborative and Socially-Aware Future Transportation

Zilin Huang, Zihao Sheng, Zhengyang Wan +10

Recent advances in autonomous system simulation platforms have significantly enhanced the safe and scalable testing of driving policies. However, existing simulators do not yet ful…

cs.RO2025

VLM-SAFE: Vision-Language Model-Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving

Yansong Qu, Zilin Huang, Zihao Sheng +4

Autonomous driving policy learning with reinforcement learning (RL) is fundamentally limited by low sample efficiency, weak generalization, and a dependence on unsafe online trial-…

cs.RO20252 cited

CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models

Zihao Sheng, Zilin Huang, Yansong Qu +3

Ensuring safety in autonomous driving systems remains a critical challenge, particularly in handling rare but potentially catastrophic safety-critical scenarios. While existing res…

cs.RO20241 cited

VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving

Zilin Huang, Zihao Sheng, Yansong Qu +2

In recent years, reinforcement learning (RL)-based methods for learning driving policies have gained increasing attention in the autonomous driving community and have achieved rema…