Mechanism Analysis and Application of Human-Machine Co-driving Effect Under Severe Driving Conditions

doi:10.12068/j.issn.1005-3026.2025.20249031

Abstract

Abstract:

The mechanism for the co-driving effect （i.e.， the accuracy of vehicle path tracking and lateral stability） during human-machine co-driving under severe driving conditions is not systematic and insufficient. To address this issue， a human-machine co-driving model was established that incorporated driver state based on the dual-driving dual-control tandem human-machine co-driving framework. Moreover， a method for human-machine co-driving based on model prediction control （MPC） was designed. An in-depth study was conducted on the influence of the driver’s preview time， vehicle speed， road adhesion coefficient， driver state parameters， and controller parameters on the path tracking accuracy and lateral stability of human-machine co-driving vehicles. The results show that the vehicle path tracking accuracy and lateral stability control of human-machine co-driving vehicles under severe working conditions are mutually constrained， and a stronger ability of human-machine co-driving vehicles to resist the perturbation of factors affecting the co-driving effect means a better performance of the designed human-machine co-driving vehicle controller.

Key words: human-machine co-driving, path tracking accuracy, lateral stability, mechanism analysis, model prediction control（MPC）

CLC Number:

U 471.15

Xian-bin WANG, Wen-long BAO, Lin LI, Ying-zhe ZHANG. Mechanism Analysis and Application of Human-Machine Co-driving Effect Under Severe Driving Conditions[J]. Journal of Northeastern University(Natural Science), 2025, 46(12): 66-77.

Figures/Tables 21

Fig.1 Dual-driving and dual-control tandem human-machine co-driving framework

Fig.2 Improved driver model

Fig.3 Vehicle model

Fig.4 Human-machine co-driving strategy

Fig.5 Reference trajectory

Table 1 Vehicle parameters (taking a certainC-class human-machine co-driving sedan as an example)

参数	数值
车辆质量 $m$ /kg	1 412
$l f$ /m	1.015
$l r$ /m	1.895
$C α f$ /(N·rad^-1)	-112 600
$C α r$ /(N·rad^-1)	-94 568
$I z$ /(kg·m^-2)	1 536.7

Table 1 Vehicle parameters (taking a certainC-class human-machine co-driving sedan as an example)

参数	数值
车辆质量 $m$ /kg	1 412
$l f$ /m	1.015
$l r$ /m	1.895
$C α f$ /(N·rad^-1)	-112 600
$C α r$ /(N·rad^-1)	-94 568
$I z$ /(kg·m^-2)	1 536.7

Fig.6 Tracking accuracy at different preview time

Fig.7 Lateral stability at different preview time

Fig.8 Tracking accuracy at different speeds

Fig.9 Lateral stability at different speeds

Fig.10 Tracking accuracy under different road adhesion coefficients

Fig.11 Lateral stability under different road adhesion coefficients

Table 2 Driver state parameters

参数	状态1	状态2	状态3	状态4	状态5
$t d$	0.1	0.2	0.2	0.2	0.3
$t h$	0.1	0.1	0.2	0.2	0.2
$t c$	0.4	0.4	0.4	0.3	0.3

Table 2 Driver state parameters

参数	状态1	状态2	状态3	状态4	状态5
$t d$	0.1	0.2	0.2	0.2	0.3
$t h$	0.1	0.1	0.2	0.2	0.2
$t c$	0.4	0.4	0.4	0.3	0.3

Fig.12 Tracking accuracy under different driver states

Fig.13 Lateral stability under different driver states

Table 3 Controller parameters

工况	N_p	N_c	状态权重 Q	控制权重 R
工况1	80	60	[1 0 0 0;0 1 0 0;0 0 2 0;0 0 0 5]	[1]
工况2	80	60	[1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]	[1]
工况3	80	60	[2 0 0 0;0 5 0 0;0 0 1 0;0 0 0 1]	[1]

Fig.14 Tracking accuracy under different controller parameters

Fig.15 Lateral stability under different controller parameters

Table 4 Comparison of human-machine co-driving effects with different controller parameters

控制器参数工况	侧向位移误差绝对值均值	方向角度误差绝对值均值	侧向加速度误差绝对值均值	横摆角速度误差绝对值均值
控制器参数工况	m	( $°$ )	m·s^-2	( $°$ )·s^-1
工况1	0.169 7	1.386 0	0.853	1.988 7
工况2	0.194 7	1.441 6	0.839	1.828 5
工况3	0.236 7	1.468 7	0.834	1.719 2

Table 4 Comparison of human-machine co-driving effects with different controller parameters

控制器参数工况	侧向位移误差绝对值均值	方向角度误差绝对值均值	侧向加速度误差绝对值均值	横摆角速度误差绝对值均值
控制器参数工况	m	( $°$ )	m·s^-2	( $°$ )·s^-1
工况1	0.169 7	1.386 0	0.853	1.988 7
工况2	0.194 7	1.441 6	0.839	1.828 5
工况3	0.236 7	1.468 7	0.834	1.719 2

Fig.16 Resistance to road adhesion coefficient disturbance: tracking accuracy

Fig.17 Resistance to road adhesion coefficient disturbance: lateral stability

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