The invention discloses an automatic driving behavior decision-making method based on deep reinforcement learning. The method comprises the steps that the current environment state around an automaticdriving vehicle is acquired; and according to the input current environment state and the current behavior state of the automatic driving vehicle, the action behavior of the automatic driving vehicleis selected and outputted in the experience pool, and if the action behavior corresponding to the current environment state does not exist in the experience pool, the action behavior of the automaticdriving vehicle is calculated and outputted by the deep reinforcement learning structure. The RGB camera, the infrared camera and the solid-state laser radar are adopted to acquire the current environment state, so that the use of sensors is reduced. An experience pool is formed by simulating and learning the driving experience of a human driver, so that the automatic driving vehicle is closer tothe driving habit of human, the problem that a manned vehicle and an unmanned vehicle coexist on the road is solved, and more importantly, the safety is improved.

    本发明公开了基于深度强化学习的自动驾驶行为决策方法,包括:获取自动驾驶车辆周围的当前环境状态;根据输入的当前环境状态和自动驾驶车辆的当前行为状态,在经验池中选择并输出自动驾驶车辆的动作行为,如果经验池中没有与当前环境状态对应的动作行为,则由深度强化学习结构计算并输出自动驾驶车辆的动作行为。本发明的获取当前环境状态采用RGB摄像头、红外摄像头和固态激光雷达,减少了传感器的使用。通过模仿学习人类驾驶员的驾驶经验形成经验池,使得自动驾驶车辆更接近人类的驾驶习惯,有利于解决有人车和无人车在路上并存的问题,更重要的是提升了安全性。


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    Title :

    Automatic driving behavior decision-making method based on deep reinforcement learning


    Additional title:

    基于深度强化学习的自动驾驶行为决策方法


    Contributors:
    YANG MINGZHU (author) / LIU XIANGWEI (author) / LI ZHUOLUO (author)

    Publication date :

    2020-09-01


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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