This paper proposes a new strategy for collision avoidance system leveraging Time-to-Collision (TTC) metrics for handling cut-in scenarios, which are particularly challenging for autonomous vehicles (AVs). By integrating a deep learning with TTC calculations, the system predicts potential collisions and determines appropriate evasive actions compared to traditional TTC -based approaches.

翻译：本文提出了一种新的碰撞规避系统策略，利用碰撞时间（TTC）度量来处理切入场景，这对自动驾驶车辆（AVs）尤其具有挑战性。通过将深度学习与TTC计算相结合，该系统能够预测潜在碰撞并确定适当的规避动作，相较于传统的基于TTC的方法有所改进。