基于仿真实验的线性驱动模型辨识

András Mihály, P. Gáspár
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引用次数: 14

摘要

提出了一种基于仿真实验的驾驶员模型识别方法。在模拟器的实时驾驶过程中,可以通过测量车辆运动和环境的适当信号来模拟驾驶员的视觉和前庭感知。然后使用线性差分自回归模型结构和最小二乘估计技术估计不同驱动程序的参数。识别的目的是用结构相似的驾驶员模型的参数来描述不同的驾驶员行为。通过使用与模拟器实验中相同的激励信号,并比较驱动器的测量输出和模拟输出,验证了所识别的驱动器模型。本文的主要新颖之处在于采用了实时模拟器的识别方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of a linear driver model based on simulator experiments
The paper presents a driver model identification method based on simulator experiments. The visual and vestibular perception of the driver can be modeled by measuring proper signals of the vehicle motion and the environment during the real-time driving of the simulator. The parameters of different drivers are then estimated using a linear difference autoregressive model structure and least-squares estimation techniques. The aim of the identification is to describe the different driver behaviors with the parameters of a driver model with similar structure. The identified driver models are validated by simulation using the same excitation signals as in the simulator experiment and comparing the measured and simulated output of the driver. The main novelty of the paper is the identification method in which a real-time simulator is used.
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