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Predicting future trajectories of surrounding agents is essential forsafety-critical autonomous driving. Most existing work focuses on predictingmarginal trajectories for each agent independently. However, it has rarely beenexplored in predicting joint trajectories for interactive agents. In this work,we propose Bi-level Future Fusion (BiFF) to explicitly capture futureinteractions between interactive agents. Concretely, BiFF fuses the high-levelfuture intentions followed by low-level future behaviors. Then thepolyline-based coordinate is specifically designed for multi-agent predictionto ensure data efficiency, frame robustness, and prediction accuracy.Experiments show that BiFF achieves state-of-the-art performance on theinteractive prediction benchmark of Waymo Open Motion Dataset.

BiFF: Bi-level Future Fusion with Polyline-based Coordinate for Interactive Trajectory Prediction