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Beyond Safe Execution: Safe Online Reinforcement Learning for Autonomous Driving with Value Calibration and Adaptive Guidance
Zeqiao Li, Yijing Wang, Haoyu Wang +2
Online reinforcement learning (RL) enables driving policies to adapt to changing deployment conditions, but requires safe exploration throughout training. Safety filtering alone do…
Posterior-Averaged Bellman Flow Matching for Distributional Critics
Zeqiao Li, Yijing Wang, Haoyu Wang +2
Distributional critics model the full return distribution, providing richer signals for exploration and risk-sensitive control. Recent work has shown that flow-based critics can mo…
DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection
Haifa Zhang, Yijing Wang, Peixi Peng +1
In autonomous driving perception, the fusion of LiDAR and camera modalities has become the dominant paradigm for 3D object detection. However, current multi-modal frameworks heavil…
PathPainter: Transferring the Generalization Ability of Image Generation Models to Embodied Navigation
Yijin Wang, Yuru Tian, Xijie Huang +5
Bird's-eye-view (BEV) images have been demonstrated to provide valuable prior information for navigation. Given the global information provided by such views, two key challenges re…
Dual-Interaction-Aware Cooperative Control Strategy for Alleviating Mixed Traffic Congestion
Zhengxuan Liu, Yuxin Cai, Yijing Wang +3
As Intelligent Transportation System (ITS) develops, Connected and Automated Vehicles (CAVs) are expected to significantly reduce traffic congestion through cooperative strategies,…
Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
Zeqiao Li, Yijing Wang, Haoyu Wang +2
Diffusion policies are expressive yet incur high inference latency. Flow Matching (FM) enables one-step generation, but integrating it into Maximum Entropy Reinforcement Learning (…