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基于二次Lasso回归的纵向驾驶员模型研究
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Research on a Longitudinal Driver Model Based on Quadratic-Lasso Regression
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    为了更好地模拟实际驾驶员行为,提出基于二次回归和 Lasso回归方法的纵向驾 驶员回归模型. 通过采集纵向驾驶行为数据,提取可能影响驾驶行为的状态参数,进而建立二 次回归驾驶员模型;面向多参数回归模型中的多重共线问题,采用Lasso回归方法进行状态参 数筛选;结合筛选数据建立二次回归驾驶员模型. 为了验证模型的有效性,与PI驾驶员模型和 一次 Lasso回归驾驶员模型进行仿真对比 . 仿真结果表明,相较于其他两种模型,所建立的驾 驶员模型具备良好的工况跟随效果,同时能较好地反映实际驾驶行为特征.

    Abstract:

    To better simulate the real driver behavior, a longitudinal driver regression model based on quadratic regression and the Lasso regression method is proposed. Firstly, by collecting longitudinal driving behavior data, state parameters that may affect driving behavior are extracted, and a quadratic regression driver model was estab? lished. Then, the Lasso regression method is applied to screen the state parameters for the multicollinearity problem in the multi-parameter regression model. Finally, a quadratic regression driver model is developed based on the screened data. In order to verify the effectiveness of the model, a simulation comparison is made between the pro? posed model and PI driver and Lasso regression driver models. The simulation results show the driver model devel? oped here not only has a better effect on driving cycle traction when compared with the other two models but can also better reflect the characteristics of actual driving behavior.

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刘通 ,曾小华 ?,李泰祥 ,宋大凤 ,庄晓 .基于二次Lasso回归的纵向驾驶员模型研究[J].湖南大学学报:自然科学版,2022,49(8):54~60

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  • 在线发布日期: 2022-09-07
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