The invention discloses a driver driving behavior automatic analysis method based on a long-term and short-term memory network. The method comprises the steps that step one, feature data is extractedand preprocessed; step two, a sliding window is designed; and step three, a driving behavior automatic analysis network is established. The method particularly comprises the following steps that firstly, driving data containing driving behaviors of a driver is extracted from an automobile CAN bus; the driving behaviors of the driver are scored by using the riding experience of a passenger, and theriding experience is taken as a label for evaluating the driving data of the driver; a driver driving behavior automatic analysis network is established based on the long-term and short-term memory network, deep training of the driving data and label data of a large number of drivers is carried out, driving behavior habits of the drivers are learned, and a driving behavior automatic analysis library is established; and finally, when any driver drives an automobile, the established driver driving behavior automatic analysis network can achieve automatic analysis of the driver driving behaviorsaccording to the driving data and judge whether the driver has an excellent driving behavior habit or not.
本发明公开了一种基于长短期记忆网络的司机驾驶行为自动化分析方法,步骤1,特征数据的提取和预处理;步骤2,滑动窗口的设计;步骤3,驾驶行为自动化分析网络的搭建。本发明首先从汽车CAN总线提取含有司机驾驶行为的行车数据;然后利用乘客的乘车体验对司机驾驶行为进行打分,并将其作为司机行车数据评价的标签;随后基于长短期记忆网络搭建司机驾驶行为自动化分析网络,并对大量司机的行车数据和标签数据进行深度训练,学习司机驾驶行为习惯,建立驾驶行为自动化分析库;最后,当任意司机驾驶汽车时,构建的司机驾驶行为自动化分析网络都能够根据其行车数据实现司机驾驶行为的自动化分析,判断司机是否具有优秀的驾驶行为习惯。
Driver driving behavior automatic analysis method based on long-term and short-term memory network
基于长短期记忆网络的司机驾驶行为自动化分析方法
2020-12-11
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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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