首页> 外国专利> METHOD AND DEVICE FOR ATTENTION-DRIVEN RESOURCE ALLOCATION BY USING REINFORCEMENT LEARNING AND V2X COMMUNICATION TO THEREBY ACHIEVE SAFETY OF AUTONOMOUS DRIVING

METHOD AND DEVICE FOR ATTENTION-DRIVEN RESOURCE ALLOCATION BY USING REINFORCEMENT LEARNING AND V2X COMMUNICATION TO THEREBY ACHIEVE SAFETY OF AUTONOMOUS DRIVING

机译:利用强化学习和V2X通讯实现自主驾驶安全性的注意力驱动资源分配方法和装置

摘要

A method for achieving better performance in an autonomous driving while saving computing powers, by using confidence scores representing a credibility of an object detection which is generated in parallel with an object detection process is provided. And the method includes steps of: (a) a computing device acquiring at least one circumstance image on surroundings of a subject vehicle, through at least one image sensor installed on the subject vehicle; (b) the computing device instructing a Convolutional Neural Network(CNN) to apply at least one CNN operation to the circumstance image, to thereby generate initial object information and initial confidence information on the circumstance image; and (c) the computing device generating final object information on the circumstance image by referring to the initial object information and the initial confidence information with a support of a Reinforcement Learning(RL) agent, and through V2X communications with at least part of surrounding objects.
机译:提供了一种通过使用表示与物体检测过程并行生成的物体检测的可信度的置信度得分来在自动驾驶中实现更好的性能同时节省计算能力的方法。并且该方法包括以下步骤:(a)计算设备通过安装在目标车辆上的至少一个图像传感器来获取目标车辆周围的至少一个情况图像; (b)计算设备指示卷积神经网络(CNN)对环境图像进行至少一个CNN操作,从而在环境图像上生成初始目标信息和初始置信度信息; (c)计算设备通过在强化学习(RL)代理的支持下参考初始对象信息和初始置信度信息,并通过与至少部分周围对象的V2X通信,在情况图像上生成最终对象信息。

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