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

METHOD AND DEVICE FOR ATTENTION-DRIVEN RESOURCE ALLOCATION BY USING AVM AND REINFORCEMENT LEARNING TO THEREBY ACHIEVE SAFETY OF AUTONOUMOUS DRIVING

机译:通过使用AVM和增强学习从而实现自动驾驶安全性的注意力驱动资源分配的方法和设备

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 panorama view 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 an RL agent.
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全景视图传感器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)计算装置在RL代理的支持下,通过参考初始物体信息和初始置信度信息,在环境图像上生成最终物体信息。

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