论文标题
重要的是您的注意：代理人对自动驾驶的重要性预测
Importance is in your attention: agent importance prediction for autonomous driving
论文作者
论文摘要
轨迹预测是自主驾驶中的重要任务。最先进的轨迹预测模型通常使用注意机制来对代理之间的相互作用进行建模。在本文中，我们表明，此类模型的注意力信息也可以用来衡量每个代理在自我车辆未来计划的轨迹方面的重要性。我们对NUPLANS数据集的实验结果表明，我们的方法可以通过对自我计划的影响有效地找到并对周围的代理进行排名。
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.
