HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling
Xin Huang,Guy Rosman,Igor Gilitschenski,Ashkan Jasour,Stephen G. McGill,John J. Leonard,Brian C. Williams,Xin Huang,Guy Rosman,Igor Gilitschenski,Ashkan Jasour,Stephen G. McGill,John J. Leonard,Brian C. Williams
Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicting continuous trajectories, to improve accuracy and support explainability. However, these approaches often assume the intent to remain fixed over the prediction horizon, which is problematic in practice, especially over...
