The invention discloses an automatic driving decision-making system based on multi-modal perception and layered actions. The automatic driving decision-making system comprises a data preprocessing module, a state characterization module, an actor reviewer module, a mixed reward function module and a multi-process training module. The training speed of the model is increased and the training performance of the model is improved through parallel training. The method is better in applicability, various sensors and a deep learning algorithm are used for comprehensively sensing the surrounding environment information, so that the automatic driving vehicle can better deal with some emergencies, and the automatic driving vehicle can more quickly and better extract useful features through a lane-divided cross-modal aggregation model. The reinforcement learning model based on the layered action can better optimize the lane keeping behavior and the lane changing behavior of the automatic driving vehicle. The safety, efficiency and comfort of each decision of the autonomous vehicle are met, traffic flow fluctuation caused by rapid speed change and lane change of the autonomous vehicle is reduced, and the traffic efficiency and traffic flow stability of the whole traffic flow are improved.
本发明公开了一种基于多模态感知和分层动作的自动驾驶决策系统,包括数据预处理模块、状态表征模块、演员评论家模块、混合奖励函数模块和多进程训练模块;通过并行训练来加快模型的训练速度和提升模型的训练表现。本发明的适用性更好,运用了多种传感器和深度学习算法来对周围环境信息进行一个全面的感知,从而让自动驾驶车能够更好的应对一些突发情况,分车道的跨模态聚合模型让自动驾驶车能够更快更好地提取有用的特征。基于分层动作的强化学习模型更好地优化自动驾驶车的车道保持行为和变道行为。满足自动驾驶车每一次决策的安全性、效率性和舒适性,并减少由于自动驾驶车急剧的变速和变道引发的车流波动,提升整个车流的交通效率和车流稳定。
Automatic driving decision-making system based on multi-modal perception and hierarchical action
一种基于多模态感知和分层动作的自动驾驶决策系统
2023-07-25
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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