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

• URL: http://arxiv.org/abs/2204.09121v1
• Date: Tue, 19 Apr 2022 20:34:30 GMT
• Title: Importance is in your attention: agent importance prediction for autonomous driving
• Authors: Christopher Hazard, Akshay Bhagat, Balarama Raju Buddharaju, Zhongtao Liu, Yunming Shao, Lu Lu, Sammy Omari, Henggang Cui
• Abstract summary: Trajectory prediction is an important task in autonomous driving. We show that attention information can also be used to measure the importance of each agent with respect to the ego vehicle's future planned trajectory.
• Score: 4.176937532441124
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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 impact on the ego's plan.

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