5 papers
TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction
Haibo Hu, Jianghuai Deng, Chen Tang +3
Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map construction are limited by a cro…
OmniSCS: Omni Safety-Critical Scenario Synthesis for Autonomous Driving via a Fully Editable Driving World
Xiaoyun Dong, Qian Xu, Yang Lu +3
The synthesis of safety-critical scenarios (SCS) and their evaluation through closed-loop simulations are crucial for developing robust autonomous driving systems. A key aspect of…
SATMapTR: Satellite Image Enhanced Online HD Map Construction
Bingyuan Huang, Guanyi Zhao, Qian Xu +3
High-definition (HD) maps are evolving from pre-annotated to real-time construction to better support autonomous driving in diverse scenarios. However, this process is hindered by…
Asymmetry Vulnerability and Physical Attacks on Online Map Construction for Autonomous Driving
Yang Lou, Haibo Hu, Qun Song +5
High-definition maps provide precise environmental information essential for prediction and planning in autonomous driving systems. Due to the high cost of labeling and maintenance…
VLM-C4L: Continual Core Dataset Learning with Corner Case Optimization via Vision-Language Models for Autonomous Driving
Haibo Hu, Jiacheng Zuo, Yang Lou +6
With the widespread adoption and deployment of autonomous driving, handling complex environments has become an unavoidable challenge. Due to the scarcity and diversity of extreme s…