2 citations · 2 across the 4 of their papers we have counts for
5 papers
Autoregressive End-to-End Planning with Time-Invariant Spatial Alignment and Multi-Objective Policy Refinement
Jianbo Zhao, Taiyu Ban, Xiangjie Li +5
The inherent sequential modeling capabilities of autoregressive models make them a formidable baseline for end-to-end planning in autonomous driving. Nevertheless, their performanc…
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation
Jianbo Zhao, Taiyu Ban, Xiyang Wang +6
Controllable trajectory generation guided by high-level semantic decisions, termed meta-actions, is crucial for autonomous driving systems. A significant limitation of existing fra…
DRoPE: Directional Rotary Position Embedding for Efficient Agent Interaction Modeling
Jianbo Zhao, Taiyu Ban, Zhihao Liu +7
Accurate and efficient modeling of agent interactions is essential for trajectory generation, the core of autonomous driving systems. Existing methods, scene-centric, agent-centric…
KiGRAS: Kinematic-Driven Generative Model for Realistic Agent Simulation
Jianbo Zhao, Jiaheng Zhuang, Qibin Zhou +7
Trajectory generation is a pivotal task in autonomous driving. Recent studies have introduced the autoregressive paradigm, leveraging the state transition model to approximate futu…
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
Diankun Zhang, Guoan Wang, Runwen Zhu +15
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system. Despite simplicity and clarity, the performance of end-to-end autonomous driv…