The invention discloses a vehicle position prediction modeling method based on a simulated driver and the method comprises the following steps: carrying out a first-stage driving simulation test, carrying out the driving simulation test through a driving simulator, and collecting the lateral speed, lateral acceleration, lateral coordinates, longitudinal speed, longitudinal acceleration and longitudinal coordinates of a vehicle; processing vehicle data collected by the first-stage simulation driving test; classifying the processed vehicle data by using a KMeans algorithm; for the classified vehicle data, establishing a transverse displacement prediction model and a longitudinal displacement prediction model by using a Gaussian process regression algorithm; and carrying out a second-stage simulation driving test, testing the established Gaussian regression model, and outputting a vehicle position prediction model composed of the transverse displacement prediction model and the longitudinal displacement prediction model if the test is qualified. Te simulated driver is used for carrying out a simulated driving test to realize vehicle position prediction modeling, the calculated amountis small, real vehicle testing is not needed, and the cost is reduced.
本发明公开一种基于模拟驾驶器的车辆位置预测建模方法,包括以下步骤:进行第一阶段模拟驾驶试验,使用驾驶模拟器进行模拟驾驶试验并采集车辆的横向速度、横向加速度、横向坐标和纵向速度、纵向加速度、纵向坐标;处理第一阶段模拟驾驶试验所采集的车辆数据;使用K‑Means算法对处理后的车辆数据进行分类;对分类后的车辆数据,使用高斯过程回归算法建立横向位移预测模型和纵向位移预测模型;进行第二阶段模拟驾驶试验,测试所建立的高斯回归模型,测试合格则输出由横向位移预测模型和纵向位移预测模型共同组成的车辆位置预测模型。本发明运用模拟驾驶器进行模拟驾驶试验实现车辆位置预测建模,计算量小,且不需要实车测试,降低了成本。
Vehicle position prediction modeling method based on simulated driver
一种基于模拟驾驶器的车辆位置预测建模方法
2021-02-02
Patent
Elektronische Ressource
Chinesisch
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