Method for calculating driving strategy of pilotless automobile in urban traffic scene

The invention relates to the field of machine learning, and discloses a method for calculating a driving strategy of a pilotless automobile in an urban traffic scene, which comprises the following steps: collecting data samples, and preprocessing the data samples to obtain a data set; constructing and training a multi-scale prediction convolutional neural network based on the data set; inputting an image acquired by the camera into a multi-scale prediction convolutional mental network, and acquiring a target category and confidence in a scene; identifying a traffic scene according to the target category; and calculating a driving strategy risk degree and moral intensity based on the traffic scene, and generating a driving strategy. According to the invention, the recognition precision and overall efficiency of the target object are improved, and the target category in the image is recognized while the precision of the recognized target is calculated. 本发明涉及机器学习领域，公开了一种无人驾驶汽车在城市交通场景中驾驶策略计算方法，包括：收集数据样本，并对数据样本进行预