MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Querying

arXiv:2306.17770v2 Announce Type: replace
Abstract: Motion prediction is crucial for autonomous driving systems to understand complex driving scenarios and make informed decisions. However, this task is challenging due to the diverse behaviors of traffic participants and complex environmental contexts. In this paper, we propose Motion TRansformer (MTR) frameworks to address these challenges. The initial MTR framework utilizes a transformer encoder-decoder structure with learnable intention queries, enabling efficient and accurate prediction of future trajectories. By customizing intention queries for distinct motion …

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