GRANP: A Graph Recurrent Attentive Neural Process Model for Vehicle Trajectory Prediction

arXiv:2404.08004v1 Announce Type: new
Abstract: As a vital component in autonomous driving, accurate trajectory prediction effectively prevents traffic accidents and improves driving efficiency. To capture complex spatial-temporal dynamics and social interactions, recent studies developed models based on advanced deep-learning methods. On the other hand, recent studies have explored the use of deep generative models to further account for trajectory uncertainties. However, the current approaches demonstrating indeterminacy involve inefficient and time-consuming practices such as sampling from trained models. To fill this …

arxiv cs.lg cs.ro graph prediction process trajectory type