The invention discloses a driver acceleration intention modeling method based on a GM-HMM, and the method comprises the steps: carrying out a simulation driving test, and collecting data which comprise an accelerator pedal travel, an accelerator pedal travel derivative and a longitudinal acceleration; extracting data and carrying out normalization processing; clustering through a K-Means clustering algorithm to obtain three central points of the acceleration intention; obtaining a slow acceleration data set, a normal acceleration data set and a sharp acceleration data set according to the center coordinates of the three acceleration intentions; training a GM-HMM model by using the training data to obtain three acceleration intention models based on the GM-HMM: a slow acceleration intentionmodel, a normal acceleration intention model and an aggressive acceleration intention model; testing the model. The driver acceleration intention model based on the GM-HMM is established by simulating the driving test and collecting data, and the method has the advantages of being high in prediction accuracy and low in cost.
本发明公开了一种基于GM‑HMM的驾驶员加速意图建模方法,该建模方法的步骤包括:进行模拟驾驶试验并采集数据,采集的数据包括加速踏板行程、加速踏板行程导数和纵向加速度;提取数据并进行归一化处理;通过K‑Means聚类算法进行聚类,得到三个加速意图的中心点;根据三个加速意图的中心坐标,得到缓慢加速数据集、正常加速数据集和激进加速数据集;使用训练数据训练GM‑HMM模型,得到三个基于GM‑HMM的加速意图模型:缓慢加速意图模型、正常加速意图模型和激进加速意图模型;测试模型。通过模拟驾驶试验采集数据,建立基于GM‑HMM的驾驶员加速意图模型,具有预测准确度高,成本低廉的优点。
Driver acceleration intention modeling method based on GM-HMM
一种基于GM-HMM的驾驶员加速意图建模方法
2021-02-23
Patent
Electronic Resource
Chinese
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