歩行者と車の相互作用を考慮するアテンションモデルによる軌道予測

Abstract

In order to realize safe automatic driving in urban areas where many kinds of moving objects move freely, it is necessary to predict the future behavior of moving objects. We propose a new trajectory prediction method based on the encoder-decoder framework, which can consider the interaction of moving objects in many aspects. By using labels and angular velocities for each moving object as inputs to the model and incorporating the interaction of moving objects using multi-head attention, the prediction accuracy is improved from the previous method.

Publication
日本機械学会ロボティクス・メカトロニクス講演会2022講演論文集
Yusuke Tamura
Yusuke Tamura
Associate Professor, PhD

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