The invention provides a rider-oriented automatic driving collision avoidance method and system. The method comprises the following steps: acquiring self-vehicle state information and surrounding environment state information in real time; wherein the surrounding environment state information comprises static obstacles, dynamic obstacles and road sign related information, and the dynamic obstacles at least comprise dynamic riders; on the basis of the obtained self-vehicle state data and the surrounding environment state data, through a pre-trained deep reinforcement learning model, self-vehicle output actions are obtained, and collision avoidance of the self-vehicle is achieved; wherein a reward function of the deep reinforcement learning model is obtained based on a difference value between a reference reward and a risk reward of the current position of the vehicle, and the risk reward of the current position of the vehicle is obtained based on obtained static obstacle related information, dynamic obstacle related information and road sign related information. The dynamic obstacle related information is obtained through a pre-constructed risk assessment model based on a driving risk field, and the dynamic obstacle related information comprises predicted future actions of the dynamic obstacle.
本公开提供了一种面向骑行者的自动驾驶避撞方法及系统,包括:实时获取自车状态信息和周围环境状态信息;其中,所述周围环境状态信息包括静态障碍物、动态障碍物以及道路标志相关信息,所述动态障碍物至少包括动态骑行者;基于获得的自车状态数据和周围环境状态数据,通过预先训练的深度强化学习模型,获得自车输出动作,实现自车的避撞;其中,所述深度强化学习模型的奖励函数基于基准奖励与自车当前位置的风险奖励的差值得到,所述自车当前位置的风险奖励的获取,基于获得的静态障碍物相关信息、动态障碍物相关信息、以及道路标志相关信息,通过预先构建的基于行车风险场的风险评估模型得到,所述动态障碍物相关信息包括预测的动态障碍物的未来动作。
Rider-oriented automatic driving collision avoidance method and system
一种面向骑行者的自动驾驶避撞方法及系统
29.11.2024
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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