The invention discloses a deep learning-based intelligent auxiliary driving method for an electric vehicle, and the method comprises the following steps: 1, collecting image information around a vehicle through a collection module, and sensing the surrounding environment and state of the vehicle; the collected data is processed through the processing center; 2, judging whether an obstacle exists in the driving track or not through an obstacle feature extraction and calculation module, extracting motion features of an object which is identified as the obstacle, and carrying out related calculation; the beneficial effects of the invention are that the deep belief network of the deep learning method is utilized to carry out feature extraction on the collected signals through an alternative unsupervised and supervised learning process method, the output of the last hidden layer is used as the input of the SVM, and the feature information is classified, trained and recognized. And finally, obstacle recognition is realized by adopting a template matching method, so that the detection and pre-judgment speed is improved, and the real-time requirement of vehicle-mounted obstacle detection in different environments is met.
本发明公开了一种深度学习的电动汽车智能辅助驾驶方法,所述方法如下:步骤一:通过采集模块采集车辆周围图像信息,感知车辆周围环境和状态;采集的数据通过处理中心进行处理;步骤二:通过障碍物特征提取计算模块判断行车轨迹中是否存在障碍物,提取被认定为障碍物的物体运动特征并进行相关计算;本发明的有益效果是:利用深度学习方法的深度信念网络通过一种交替进行的无监督和有监督学习过程的方法对采集的信号进行特征提取,将最后一层隐含层的输出作为SVM的输入,对特征信息进行分类训练识别,最后采用模板匹配法实现障碍物识别,提高了检测和预判速度,适应不同环境下车载障碍物检测的实时性要求。
Deep learning electric vehicle intelligent auxiliary driving method
一种深度学习的电动汽车智能辅助驾驶方法
2023-08-25
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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