The invention discloses a TD3 unmanned driving decision-making method based on a multi-experience playback pool, and the method comprises the steps: constructing an unmanned driving decision-making model which comprises a state space and an action space of an intelligent vehicle; setting a reward mechanism based on the demand of the unmanned driving decision model; constructing a multi-experience playback pool, and setting a multi-experience sampling strategy; combining the state space, the action space, the reward mechanism, the multi-experience sampling strategy and a deep reinforcement learning algorithm TD3, and constructing a TD3 unmanned driving decision model based on a multi-experience playback pool; and making a decision on the action of the unmanned vehicle in a complex scene by using the TD3 unmanned decision model based on the multi-experience playback pool. According to the method, the convergence speed of the TD3 unmanned driving decision model in a complex scene can be effectively improved, and the safety of unmanned driving decision is improved.

    本发明公开了基于多重经验回放池的TD3无人驾驶决策方法,包括:构建无人驾驶决策模型,其中,所述无人驾驶决策模型包括智能车辆的状态空间和动作空间;基于所述无人驾驶决策模型的需求,设置奖励机制;构建多重经验回放池,并设置多重经验采样策略;将所述状态空间、所述动作空间、所述奖励机制、所述多重经验采样策略与深度强化学习算法TD3进行结合,构建基于多重经验回放池的TD3无人驾驶决策模型;利用所述基于多重经验回放池的TD3无人驾驶决策模型,对无人驾驶车辆在复杂场景中的动作做出决策。本发明能够有效提升TD3无人驾驶决策模型在复杂场景中的收敛速度,提高无人驾驶决策的安全性。


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    Titel :

    TD3 unmanned driving decision-making method based on multi-experience playback pool


    Weitere Titelangaben:

    基于多重经验回放池的TD3无人驾驶决策方法


    Beteiligte:
    DU YU (Autor:in) / JIANG ANNI (Autor:in) / ZHANG HAO (Autor:in) / ZHAO SHIXIN (Autor:in) / GAO QIUQI (Autor:in)

    Erscheinungsdatum :

    27.08.2024


    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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