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Author

Ziran Wang

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Preprint Oct 2026

Online Constraint Optimization-Based Indirect-Adaptive Robust Control for Autonomous Vehicles with Unknown Friction

Friction uncertainty is a significant challenge for autonomous vehicle control, undermining feasibility and performance. This paper proposes a novel two-layer control framework to achieve vehicle motion control under large friction uncertainty by combining optimization-based planning with indirect adaptive robust contr...

Yu-Peng Zhou, I-Chia Chang, Zi-Ran Wang et al. · 0 citations
Preprint Sep 2026

Designing Versatile Samples for Learned Trajectory Scoring

This work designs a training dataset that provides more informative supervision for the scorer and constructs two generators that perturb the logged human trajectory along the two axes a vehicle can be displaced: laterally toward the drivable boundary and longitudinally toward a leading vehicle.

Ya-Guang Li, Jia-Ru Zhang, Chu-Heng Wei et al. · 0 citations
Preprint Aug 2026

How Can Driving World Models Do Counterfactual Prediction?

This paper identifies a fundamental mismatch between direct action-conditioned prediction and counterfactual ground truth in driving world models, and introduces a deliberately simple, training-free pipeline that moves observed evidence into the counterfactual view and lets the frozen model complete what remains unknow...

Jiaru Zhang, C. Cui, Yi Xu et al. · 0 citations
Review Open access Aug 2026

Generative AI for Autonomous Driving: Frontiers and Opportunities

This survey delivers a comprehensive and critical synthesis of the emerging role of GenAI across the autonomous driving stack, delving into the frontier applications of GenAI in image, LiDAR, trajectory, occupancy, and video generation, as well as LLM-guided reasoning and decision-making.

Yu-Ping Wang, Shuo Xing, C. Cui et al. · 60 citations · ⚡2
Review Jul 2026

Post-Training in End-to-End Autonomous Driving

A unified view of post-training for autonomous driving is presented by defining its scope and organizing the existing literature into four major families based on the form of supervision they use, which aim to facilitate a systematic understanding of this emerging area and stimulate future research on reliable and effi...

Ruining Yang, Mu Wang, Yi-Xiao Chen et al. · 1 citation

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