The invention provides an adaptive cruise control method and system based on deep reinforcement learning. A driver car-following style identification module established based on a BP neural network; building an ACC control model based on deep reinforcement learning; the ACC control model comprises a strategy module and a deep Q network module; dividing the vehicle following behaviors of the driver into three types of vehicle following styles and then labeling; the car-following style identification model is used for training by using a BP neural network to obtain a driver car-following style classification model, and outputting a car-following style of a driver based on the driver car-following style classification model; the strategy module establishes a Q value network, and outputs an expected acceleration for adjusting the vehicle through the Q value network according to the obtained effective characteristic performance data of the real-time vehicle following behavior; the self-adaptive cruise control method closer to the individuation of a driver is achieved, and the safety, the following performance, the comfort and the economical efficiency are high.

    本发明提供一种基于深度强化学习的自适应巡航控制方法以及系统;基于BP神经网络建立的驾驶人跟车风格辨识模块;基于深度强化学习建立的ACC控制模型;ACC控制模型包括策略模块、深度Q网络模块;将驾驶人跟车行为分为三类跟车风格然后打标签;跟车风格辨识模利用BP神经网络训练得到驾驶人跟车风格分类模型,基于驾驶人跟车风格分类模型输出驾驶人的跟车风格;所述策略模块建立Q值网络,通过Q值网络根据获取的实时跟车行为的有效特征性能数据,输出调整车辆的期望加速度;实现更接近驾驶人员个性化的自适应巡航控制方法且安全性、跟随性、舒适性、经济性高。


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    Titel :

    Adaptive cruise control method and system based on deep reinforcement learning


    Weitere Titelangaben:

    一种基于深度强化学习的自适应巡航控制方法以及系统


    Beteiligte:
    ZHENG XUELIAN (Autor:in) / HAN ZHUOCHENG (Autor:in) / REN YUANYUAN (Autor:in) / LI XIANSHENG (Autor:in) / XI JIANFENG (Autor:in) / WANG JIE (Autor:in) / LI YUANZHAO (Autor:in) / WU XUEFENG (Autor:in)

    Erscheinungsdatum :

    2023-06-13


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    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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    Multi-Objective Adaptive Cruise Control via Deep Reinforcement Learning

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    Multi-Objective Adaptive Cruise Control via Deep Reinforcement Learning

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    Multi-Objective Adaptive Cruise Control via Deep Reinforcement Learning

    Zhang, Yourong / Lin, Li / Song, Yizhou et al. | British Library Conference Proceedings | 2022