The invention provides an intelligent driving decision-making system and method based on reinforcement learning. The method comprises the following steps: mapping a decision-making action into an action space of automatic parking based on a parking control instruction; all reward factors of parking operation in the action space are determined, and then the reward track of the automobile after automatic parking is determined according to the instant reward of each reward factor; the state space of the sensor noise when the automobile is automatically parked is determined, then track matching is conducted on the parking control instruction according to the state space and the action space of the sensor noise, and the anti-interference performance of intelligent driving is obtained; and according to the reward track and anti-interference performance, determining a deviation track of the automobile after automatic parking, and when the deviation track is lower than a preset parking deviation threshold value, performing adaptive constraint adjustment on a decision action of the automobile in automatic parking. On the basis of the scheme, constraint adjustment of the automatic parking action of the automobile can be achieved, and therefore the environmental adaptability of automatic parking of the automobile can be improved.
本申请提供了一种基于强化学习的智能驾驶决策系统及方法,基于所述驻车控制指令将决策动作映射为自动驻车的动作空间;确定动作空间中驻车操作的所有奖励因素,进而由各个奖励因素的即时奖励确定自动驻车后汽车的奖励轨迹;确定汽车在自动驻车时传感器噪声的状态空间,进而根据传感器噪声的状态空间和动作空间对驻车控制指令进行轨迹匹配,得到智能驾驶的抗干扰性;依据奖励轨迹和抗干扰性确定自动驻车后汽车的偏差轨迹,当偏差轨迹低于预设的驻车偏差阈值时,对汽车在自动驻车中的决策动作进行自适应约束调整。基于上述方案可实现汽车的自动驻车动作的约束调整,从而可提高汽车自动驻车的环境适应性。
Intelligent driving decision-making system and method based on reinforcement learning
一种基于强化学习的智能驾驶决策系统及方法
2025-03-18
Patent
Electronic Resource
Chinese
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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