7 papers
FeasibleFlow: One-Step Joint Transport of Configuration Feasibility and Trajectories for End-to-End Driving
Xiang Li, Bikun Wang, Qing Xu +1
End-to-end autonomous driving maps current observations directly to future trajectories, yet those trajectories must remain valid as the scene evolves. Future state modeling aims t…
LinguaSim: Interactive Multi-Vehicle Testing Scenario Generation via Natural Language Instruction Based on Large Language Models
Qingyuan Shi, Qingwen Meng, Hao Cheng +2
The generation of testing and training scenarios for autonomous vehicles has drawn significant attention. While Large Language Models (LLMs) have enabled new scenario generation me…
Predictive Risk Analysis and Safe Trajectory Planning for Intelligent and Connected Vehicles
Zeyu Han, Mengchi Cai, Chaoyi Chen +6
The safe trajectory planning of intelligent and connected vehicles is a key component in autonomous driving technology. Modeling the environment risk information by field is a prom…
DenseFormer: Learning Dense Depth Map from Sparse Depth and Image via Conditional Diffusion Model
Ming Yuan, Chuang Zhang, Lei He +2
The depth completion task is a critical problem in autonomous driving, involving the generation of dense depth maps from sparse depth maps and RGB images. Most existing methods emp…
V2X-DGPE: Addressing Domain Gaps and Pose Errors for Robust Collaborative 3D Object Detection
Sichao Wang, Ming Yuan, Chuang Zhang +3
In V2X collaborative perception, the domain gaps between heterogeneous nodes pose a significant challenge for effective information fusion. Pose errors arising from latency and GPS…
EDRF: Enhanced Driving Risk Field Based on Multimodal Trajectory Prediction and Its Applications
Junkai Jiang, Zeyu Han, Yuning Wang +4
Driving risk assessment is crucial for both autonomous vehicles and human-driven vehicles. The driving risk can be quantified as the product of the probability that an event (such…
A Generalized Control Revision Method for Autonomous Driving Safety
Zehang Zhu, Yuning Wang, Tianqi Ke +5
Safety is one of the most crucial challenges of autonomous driving vehicles, and one solution to guarantee safety is to employ an additional control revision module after the plann…