MS-Net: A Multi-Path Sparse Model for Motion Prediction in Multi-Scenes

arXiv:2403.00353v1 Announce Type: new
Abstract: The multi-modality and stochastic characteristics of human behavior make motion prediction a highly challenging task, which is critical for autonomous driving. While deep learning approaches have demonstrated their great potential in this area, it still remains unsolved to establish a connection between multiple driving scenes (e.g., merging, roundabout, intersection) and the design of deep learning models. Current learning-based methods typically use one unified model to predict trajectories in different scenarios, which may result in sub-optimal …

abstract arxiv autonomous autonomous driving behavior cs.ai cs.cv cs.ro deep learning driving human multiple path prediction stochastic type unsolved