The invention relates to the technical field of automatic driving behavior decision-making, and discloses a safety reinforcement learning intelligent vehicle afflux decision-making method and system based on a prediction track. And constructing a reinforcement learning afflux decision model, obtaining a prediction trajectory corresponding to each action by using the prediction model, calculating the cost of each step state in the prediction trajectory based on a cost function, and calculating the total discount cost of the prediction trajectory by using a total discount cost calculation method. And determining a safety action set according to the discount total cost of each action. If the original decision action of the intelligent agent is in the safety action set or the safety action set is empty, outputting the original decision action; and if not in the safety action set, outputting the action with the maximum value in the safety action set. According to the method, the predicted trajectory is fused into safe reinforcement learning, and unsafe actions are replaced with safe actions, so that the collision frequency in the training process is effectively reduced, the training period is shortened, the training cost is reduced, and the safety of afflux decision making is improved.
本申请涉及自动驾驶行为决策技术领域,公开了一种基于预测轨迹的安全强化学习智能车汇入决策方法及系统。构建强化学习汇入决策模型,利用预测模型获取每个动作对应的预测轨迹,基于代价函数计算预测轨迹中每一步状态的代价,利用折现总代价计算方法计算预测轨迹的折现总代价。然后根据每个动作的折现总代价确定安全动作集。若智能体的原始决策动作在安全动作集中,或者安全动作集为空,则输出原始决策动作;若不在安全动作集中,则输出安全动作集中价值最大的动作。本申请中,将预测轨迹融入安全强化学习,通过将不安全动作替换为安全动作,有效地减少了训练过程中的碰撞次数,从而缩短了训练周期,降低了训练成本,提高了汇入决策的安全性。
Safety reinforcement learning intelligent vehicle afflux decision-making method and system based on prediction trajectory
基于预测轨迹的安全强化学习智能车汇入决策方法及系统
12.11.2024
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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