研究人员推出了一种用于在自动驾驶场景中预测行人意图的新框架ESIA。该方法将行人和他们的环境建模为图中的节点，利用能量函数来捕捉个体意图和交互。ESIA旨在通过确保场景级一致性并惩罚逻辑矛盾来提高预测的鲁棒性和可解释性。 AI
影响 增强了自动驾驶系统的行人意图预测能力，有望提高安全性和决策能力。
排序理由 这是一篇描述行人意图预测新框架的研究论文。
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ESIA框架增强了自动驾驶中行人意图预测能力
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- 这是一篇描述行人意图预测新框架的研究论文。
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报道来源 [1]
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ESIA：一种基于能量的时空交互感知行人意图预测框架
arXiv:2604.23728v1 Announce Type: new Abstract: Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and actions by modeling temporal dynamics, social interactions, and environmental contex…