The invention relates to an intelligent driving decision-making method and system based on deep learning. The method comprises the following steps: establishing a deep learning network model with an intelligent driving function; controlling the vehicle to automatically run by using the established deep learning network model, collecting external environment information and internal running information of the vehicle in real time to form real-time external environment data and real-time internal running data, and inputting the real-time external environment data and the real-time internal running data into a deep learning module to obtain a vehicle real-time control instruction; and controlling the vehicle to run according to the vehicle real-time control instruction. According to the invention, the decision-making process of the human brain is simulated by using the deep learning network module; input and output are connected with each other through a large number of neurons; and the deep learning network model is not based on fixed rules, has the characteristics of self-learning and self-updating, can flexibly adapt to various different environment states to realize improved effectiveness and timeliness.
本发明涉及一种基于深度学习的智能驾驶决策方法及系统,该方法包括如下步骤:建立具有智能驾驶功能的深度学习网络模型;利用所建立的深度学习网络模型控制车辆自动运行,实时采集车辆的外部环境信息和内部运行信息以形成实时外部环境数据和实时内部运行数据,将实时外部环境数据和实时内部运行数据输入深度学习模块以获取车辆实时控制指令;以及依据车辆实时控制指令控制车辆运行。本发明利用深度学习网络模块模拟人脑的决策过程,输入到输出之间通过大量的神经元相互连接,深度学习网络模型并非基于固定的规则,具有自学习和自更新的特点,可以灵活的适应于各种不同的环境状态,能够较好的兼顾有效性和时效性。
Intelligent driving decision-making method and system based on deep learning
基于深度学习的智能驾驶决策方法及系统
2020-04-17
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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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