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Method and device for optimized resource allocation in autonomous driving on the basis of reinforcement learning using data from lidar, radar, and camera sensor

机译:基于使用激光雷达,雷达和摄像头传感器的数据进行强化学习而在自动驾驶中优化资源分配的方法和装置

摘要

A method for efficient resource allocation in autonomous driving by reinforcement learning is provided for reducing computation via a heterogeneous sensor fusion. This attention-based method includes steps of: a computing device instructing an attention network to perform a neural network operation by referring to attention sensor data, to calculate attention scores; instructing a detection network to acquire video data by referring to the attention scores and to generate decision data for the autonomous driving; instructing a drive network to operate the autonomous vehicle by referring to the decision data, to acquire circumstance data, and to generate a reward by referring to the circumstance data; and instructing the attention network to adjust parameters used for the neural network operation by referring to the reward. Thus, a virtual space where the autonomous vehicle optimizes the resource allocation can be provided by the method.
机译:提供了一种用于通过强化学习在自动驾驶中进行有效资源分配的方法,用于通过异构传感器融合来减少计算量。该基于注意力的方法包括以下步骤:计算设备通过参考注意力传感器数据指示注意力网络执行神经网络操作,以计算注意力得分;以及指示检测网络通过参考注意力分数获取视频数据并生成自动驾驶决策数据;通过参考决策数据,指示驾驶网络操作自动驾驶汽车,获取情况数据,并通过参考情况数据产生奖励;并通过参考奖励指示注意力网络调整用于神经网络操作的参数。因此,通过该方法可以提供自动驾驶车辆优化资源分配的虚拟空间。

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