Importance is in your attention: agent importance prediction for autonomous driving

@article{Hazard2022ImportanceII,
  title={Importance is in your attention: agent importance prediction for autonomous driving},
  author={Christopher Hazard and Akshay Bhagat and Balarama Raju Buddharaju and Zhongtao Liu and Yunming Shao and Lu Lu and Sammy Omari and Henggang Cui},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2022},
  pages={2531-2534}
}
Trajectory prediction is an important task in autonomous driving. State-of-the-art trajectory prediction models often use attention mechanisms to model the interaction between agents. In this paper, we show that the attention information from such models can also be used to measure the importance of each agent with respect to the ego vehicle’s future planned trajectory. Our experiment results on the nuPlans dataset show that our method can effectively find and rank surrounding agents by their… 

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