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NEURAL NETWORK APPROACH FOR PARAMETER LEARNING TO SPEED UP PLANNING FOR COMPLEX DRIVING SCENARIOS

机译:用于复杂驾驶场景的参数学习的神经网络方法

摘要

In one embodiment, a computer-implemented method of operating an autonomous driving vehicle (ADV) includes perceiving a driving environment surrounding the ADV based on sensor data obtained from one or more sensors mounted on the ADV, determining a driving scenario, in response to a driving decision based on the driving environment, applying a predetermined machine-learning model to data representing the driving environment and the driving scenario to generate a set of one or more driving parameters, and planning a trajectory to navigate the ADV using the set of the driving parameters according to the driving scenario through the driving environment.
机译:在一个实施例中,一种用于操作自动驾驶车辆(ADV)的计算机实现的方法包括:基于从安装在ADV上的一个或多个传感器获得的传感器数据,感知ADV周围的驾驶环境,确定驾驶情景,以响应于基于驾驶环境的驾驶决策,将预定的机器学习模型应用于代表驾驶环境和驾驶场景的数据,以生成一组一个或多个驾驶参数,并计划使用该套驾驶对ADV进行导航的轨迹根据驾驶环境中的驾驶场景确定参数。

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