2 citations · 5 across the 15 of their papers we have counts for
11 papers · 1 filter
Hierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning
Siyi Lu, Lei He, Shengbo Eben Li +3
End-to-end autonomous driving offers a streamlined alternative to the traditional modular pipeline, integrating perception, prediction, and planning within a single framework. Whil…
Unveiling the Black Box: Independent Functional Module Evaluation for Bird's-Eye-View Perception Model
Ludan Zhang, Xiaokang Ding, Yuqi Dai +2
End-to-end models are emerging as the mainstream in autonomous driving perception. However, the inability to meticulously deconstruct their internal mechanisms results in diminishe…
Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception
Lei He, Qiaoyi Wang, Honglin Sun +5
Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…
Controllable Traffic Simulation through LLM-Guided Hierarchical Reasoning and Refinement
Zhiyuan Liu, Leheng Li, Yuning Wang +5
Evaluating autonomous driving systems in complex and diverse traffic scenarios through controllable simulation is essential to ensure their safety and reliability. However, existin…
GS-Net: Heterogeneous Vehicle Data Reuse via Generalizable Plug-and-Play 3DGS Module
Yichen Zhang, Zihan Wang, Jiali Han +5
End-to-end autonomous driving is increasingly data-driven, yet data reuse across vehicles remains limited. Each new vehicle often requires additional data collection and retraining…
Hierarchical and Decoupled BEV Perception Learning Framework for Autonomous Driving
Yuqi Dai, Jian Sun, Shengbo Eben Li +4
Perception is essential for autonomous driving system. Recent approaches based on Bird's-eye-view (BEV) and deep learning have made significant progress. However, there exists chal…
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation
Jian Sun, Yuqi Dai, Chi-Man Vong +5
Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-vie…
DenserRadar: A 4D millimeter-wave radar point cloud detector based on dense LiDAR point clouds
Zeyu Han, Junkai Jiang, Xiaokang Ding +4
The 4D millimeter-wave (mmWave) radar, with its robustness in extreme environments, extensive detection range, and capabilities for measuring velocity and elevation, has demonstrat…
Feature Map Convergence Evaluation for Functional Module
Ludan Zhang, Chaoyi Chen, Lei He +1
Autonomous driving perception models are typically composed of multiple functional modules that interact through complex relationships to accomplish environment understanding. Howe…
Neural Radiance Field in Autonomous Driving: A Survey
Lei He, Leheng Li, Wenchao Sun +5
Neural Radiance Field (NeRF) has garnered significant attention from both academia and industry due to its intrinsic advantages, particularly its implicit representation and novel…
A Risk-aware Planning Framework of UGVs in Off-Road Environment
Junkai Jiang, Zhenhua Hu, Zihan Xie +7
Planning module is an essential component of intelligent vehicle study. In this paper, we address the risk-aware planning problem of UGVs through a global-local planning framework…