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

• URL: http://arxiv.org/abs/2306.14161v2
• Date: Sat, 19 Aug 2023 07:55:10 GMT
• Title: BiFF: Bi-level Future Fusion with Polyline-based Coordinate for Interactive Trajectory Prediction
• Authors: Yiyao Zhu, Di Luan, Shaojie Shen
• Abstract summary: We propose Bi-level Future Fusion (BiFF) to capture future interactions between interactive agents. Concretely, BiFF fuses the high-level future intentions followed by low-level future behaviors. BiFF achieves state-of-the-art performance on the interactive prediction benchmark of Open Motion dataset.
• Score: 23.895217477379653
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Predicting future trajectories of surrounding agents is essential for safety-critical autonomous driving. Most existing work focuses on predicting marginal trajectories for each agent independently. However, it has rarely been explored in predicting joint trajectories for interactive agents. In this work, we propose Bi-level Future Fusion (BiFF) to explicitly capture future interactions between interactive agents. Concretely, BiFF fuses the high-level future intentions followed by low-level future behaviors. Then the polyline-based coordinate is specifically designed for multi-agent prediction to ensure data efficiency, frame robustness, and prediction accuracy. Experiments show that BiFF achieves state-of-the-art performance on the interactive prediction benchmark of Waymo Open Motion Dataset.

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