10 papers
WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving
Xuerun Yan, Zhexi Lian, Nuoheng Zhang +5
Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition or suffer from fragmented world…
A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach
Jia Hu, Yang Chang, Haoran Wang
Motion planning for autonomous driving (AD) faces a critical trade-off. While traditional rule-based pipelines offer verifiable safety and interpretability, they often fail to gene…
Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving
Zhexi Lian, Haoran Wang, Xuerun Yan +4
End-to-end autonomous driving is typically built upon imitation learning (IL), yet its performance is constrained by the quality of human demonstrations. To overcome this limitatio…
MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
Jia Hu, Zhexi Lian, Xuerun Yan +5
Autonomous Driving (AD) vehicles still struggle to exhibit human-like behavior in highly dynamic and interactive traffic scenarios. The key challenge lies in AD's limited ability t…
Anti-bullying Adaptive Cruise Control: A proactive right-of-way protection approach
Jia Hu, Zhexi Lian, Haoran Wang +6
Adaptive Cruise Control (ACC) systems have been widely commercialized in recent years. However, existing ACC systems remain vulnerable to close-range cut-ins, a behavior that resem…
Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning
Jia Hu, Mingyue Lei, Haoran Wang +2
Personalization is crucial for the widespread adoption of advanced driver assistance system. To match up with each user's preference, the online evolution capability is a must. How…