The invention provides an automatic driving transverse and longitudinal integrated decision-making method and system based on deep reinforcement learning, a storage medium and electronic equipment, and relates to the technical field of automatic driving. The method comprises the steps of collecting an automatic driving vehicle and a surrounding environment state in real time; taking the current autonomous vehicle and the surrounding environment state as the input of the deep learning model, and obtaining an action space; selecting and executing the action with the highest evaluation according to the reinforcement learning decision model by taking maximization of an expected reward as a target; and repeating the steps until the target point is reached. By collecting and processing a large amount of driving data and automatically learning and optimizing the intelligent decision-making network, various driving scenes and tasks can be quickly adapted without retraining the model, so that the accuracy and stability of decision making are improved, and a solid foundation is laid for commercialized application of the automatic driving technology.
本发明提供一种基于深度强化学习的自动驾驶横纵向一体化决策方法、系统、存储介质和电子设备,涉及自动驾驶技术领域。本发明包括实时采集自动驾驶车辆及周围环境状态;将当前的自动驾驶车辆及周围环境状态作为所述深度学习模型的输入,获取动作空间;根据所述强化学习决策模型,以最大化期望奖励为目标,选择并执行评价最高的动作;重复执行前述步骤,直至到达目标点。通过收集并处理大量的驾驶数据,自动学习和优化智能决策网络,能够快速地适应各种驾驶场景和任务,而不需要重新训练模型,从而提高了决策的准确性和稳定性,并为实现自动驾驶技术的商业化应用打下坚实的基础。
Automatic driving transverse and longitudinal integrated decision-making method based on deep reinforcement learning
基于深度强化学习的自动驾驶横纵向一体化决策方法
2023-07-25
Patent
Elektronische Ressource
Chinesisch
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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