6 papers
UnsDrive: Towards Robust End-to-End Autonomous Driving in Unstructured Scenes
Nanxin Zeng, Ruiqi Song, Xiangyu Guo +2
End-to-end planning has shown strong promise for autonomous driving, but most existing methods are designed for structured urban roads and generalize poorly to unstructured mining…
OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model
Junjie Cheng, Ruiqi Song, Ye Wu +3
Autonomous driving systems are steadily moving toward end-to-end paradigms to mitigate the limited adaptability of rule-based pipelines in complex traffic environments. However, mo…
SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
Ruiqi Song, Dujun Nie, Siyu Teng +7
Vision-Language-Action (VLA) models have become a dominant paradigm for embodied intelligence. However, most existing approaches are built on large-scale transformers, resulting in…
UnsOcc: 3D Semantic Occupancy Prediction in Unstructured Scene via Rendering Fusion
Ye Wu, Ruiqi Song, Baiyong Ding +3
Unstructured scenes present unique challenges for autonomous driving, as irregular obstacles and sparse scene layouts undermine the effectiveness of traditional perception methods…
DriveSplat: Unified Neural Gaussian Reconstruction for Dynamic Driving Scenes
Cong Wang, Ruiqi Song, Wei Tian +3
Reconstructing large-scale dynamic driving scenes remains challenging due to the coexistence of static environments with extreme depth variation and diverse dynamic actors exhibiti…
InsightDrive: Insight Scene Representation for End-to-End Autonomous Driving
Ruiqi Song, Xianda Guo, Yanlun Peng +3
Conventional end-to-end autonomous driving methods often rely on explicit global scene representations, which typically consist of 3D object detection, online mapping, and motion p…