5 papers
ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving
Benshan Ma, Pei Liu, Ruiguo Zhong +4
In interactive scenarios, an autonomous driving system is required to generate ego actions under the influence of other agents' behaviors. Existing World Action Models (WAMs) typic…
DA-WAM: Decision-Aligned Future Latents for Driving World Models
Ruiguo Zhong, Benshan Ma, Xiaolong Chen +5
World models for autonomous driving should anticipate the consequences that matter for driving decisions rather than reconstruct every detail of future scenes. However, predictive…
Traffic Sign Recognition in Autonomous Driving: Dataset, Benchmark, and Field Experiment
Guoyang Zhao, Weiqing Qi, Kai Zhang +7
Traffic Sign Recognition (TSR) is a core perception capability for autonomous driving, where robustness to cross-region variation, long-tailed categories, and semantic ambiguity is…
VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Haichao Liu, Haoren Guo, Pei Liu +4
Scene understanding and risk-aware attentions are crucial for human drivers to make safe and effective driving decisions. To imitate this cognitive ability in urban autonomous driv…
Fast and Scalable Game-Theoretic Trajectory Planning with Intentional Uncertainties
Zhenmin Huang, Yusen Xie, Benshan Ma +2
Trajectory planning involving multi-agent interactions has been a long-standing challenge in the field of robotics, primarily burdened by the inherent yet intricate interactions am…