27 citations · 35 across the 9 of their papers we have counts for
9 papers
Reasoning to Regulate: Chain-of-Thought for Traffic Rule Understanding
Yueru Luo, Xu Yan, Changqing Zhou +5
Understanding and complying with traffic regulations is a safety-critical requirement for autonomous driving, yet remains challenging due to the diversity and context dependence of…
FASTopoWM: Fast-Slow Lane Segment Topology Reasoning with Latent World Models
Yiming Yang, Hongbin Lin, Yueru Luo +7
Lane segment topology reasoning provides comprehensive bird's-eye view (BEV) road scene understanding, which can serve as a key perception module in planning-oriented end-to-end au…
TopoStreamer: Temporal Lane Segment Topology Reasoning in Autonomous Driving
Yiming Yang, Yueru Luo, Bingkun He +8
Lane segment topology reasoning constructs a comprehensive road network by capturing the topological relationships between lane segments and their semantic types. This enables end-…
Geometry-Guided Representations for Coherent Lane and Traffic Topology Reasoning in Driving Scenes
Yueru Luo, Changqing Zhou, Yiming Yang +4
Road topology reasoning is fundamental for autonomous driving, requiring both accurate perception of road elements and understanding of their complex connectivity, including lane c…
Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning
Yiming Yang, Yueru Luo, Bingkun He +5
Extracting lane topology from perspective views (PV) is crucial for planning and control in autonomous driving. This approach extracts potential drivable trajectories for self-driv…
Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D Lane Detection by Hierarchical Shape Matching
Zhihao Guan, Ruixin Liu, Zejian Yuan +6
As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict de…
A Survey on Multimodal Large Language Models for Autonomous Driving
Can Cui, Yunsheng Ma, Xu Cao +18
With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive th…
THMA: Tencent HD Map AI System for Creating HD Map Annotations
Kun Tang, Xu Cao, Zhipeng Cao +8
Nowadays, autonomous vehicle technology is becoming more and more mature. Critical to progress and safety, high-definition (HD) maps, a type of centimeter-level map collected using…
M-3DLaneNet: Exploring Multi-Modal 3D Lane Detection
Yueru Luo, Xu Yan, Chaoda Zheng +5
Estimating accurate lane lines in 3D space remains challenging due to their sparse and slim nature. Previous works mainly focused on using images for 3D lane detection, leading to…