基于神经工效学的智能车辆横向控制模型研究

doi:10.19562/j.chinasae.qcgc.2021.07.013

Abstract

Abstract:

In the process of revealing the driving mechanism of the driver， some of the existing driver models are from the perspective of driver cognition alone and the other from the perspective of control alone， so there is a lack of a system model that organically combines the driver’s cognitive process and control principle. In order to solve the above problems， a vehicle lateral control model based on neuro?ergonomics is established by integrating model predictive control （MPC） algorithm and arm muscle model based on neuro?ergonomics cognitive architecture. The model is verified by test using the CarSim/Simulink co?simulation and dSPACE/driving simulator hardware in the loop. The results show that the trajectory tracking accuracy of the vehicle lateral control model based on neuro?ergonomics is better than that of the MPC algorithm. Additionally， the control of steering wheel angle， yaw angle and lateral acceleration fluctuation amplitude is also improved compared with MPC algorithm.

Key words: lateral control model, neuro?ergonomics, model predictive control, hardware in the loop

Yingshi Guo,Hongjia Zhang,Rui Fu,Chang Wang. Research on Intelligent Vehicle Lateral Control Model Based on Neuro⁃Ergonomics[J].Automotive Engineering, 2021, 43(7): 1057-1065.

Figures/Tables 11

动力学模型参数	符号	数值
整车质量/kg	$m$	1 723
绕Z轴转动惯量/（kg·m²）	$I z$	4 175
质心至前轴的距离/m	$a$	1.232
质心至后轴的距离/m	$b$	1.468
前轮胎的侧偏刚度/（N·rad^-1）	$C c f$	66 900
后轮胎的侧偏刚度/（N·rad^-1）	$C c r$	62 700

References 21

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Research on Intelligent Vehicle Lateral Control Model Based on Neuro⁃Ergonomics

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