The invention discloses a scene-driven high-generalization federal reinforcement learning automatic driving system and a scene-driven high-generalization federal reinforcement learning automatic driving method, which are used for simulating learning experts to learn implicit expert preferences from expert demonstration and realizing multi-angle guidance of reinforcement learning student feature extraction, reward function modeling, loss function construction and group optimization in combination with dynamic driving suggestions. The problem of reinforcement learning target alignment is solved in a targeted manner; learning experts are simulated, the relation among multiple learning tasks is enhanced through cross attention, and the aerial view reconstruction process under the embedded guidance of scene depth perception and scene semantic perception is achieved. Through cross-scene optimization, specific experience sharing among different expert data distributions is realized, and high-universality imitation learning experts are trained; motion planning, reward feedback and dynamic driving suggestions are output through a proposed reward function decoder to serve as training and optimization bases of reinforcement learning students, and learning of driving rules is achieved. And through combination of the time sequence processing module and knowledge distillation, the representation capability of original image input is improved.

    本发明公开了场景驱动的高泛化性联邦强化学习自动驾驶系统及方法,模仿学习专家从专家演示中学习隐式专家偏好,结合动态驾驶建议实现对强化学习学生特征提取、奖励函数建模、损失函数构建,群体优化多角度指导,针对性解决强化学习目标对齐难题;模仿学习专家,通过交叉注意力增强多学习任务之间的联系,实现场景深度感知和场景语义感知嵌入指导下的鸟瞰图重构过程。通过跨场景优化,实现不同专家数据分布之间的特异性经验共享,训练高普适性模仿学习专家;通过提出的奖励函数解码器输出运动规划、奖励反馈和动态驾驶建议作为强化学习学生训练和优化依据,实现驾驶规则的学习。通过时序处理模块结合知识蒸馏,提高原始图像输入的表征能力。


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    Title :

    Scene-driven high-generalization federal reinforcement learning automatic driving system and method


    Additional title:

    场景驱动的高泛化性联邦强化学习自动驾驶系统及方法


    Contributors:
    LU SIKAI (author) / CAI YINGFENG (author) / WANG HAI (author) / LIU ZE (author) / LIU QINGCHAO (author) / SUN XIAOQIANG (author)

    Publication date :

    2025-04-15


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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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