Strategy decision of man-machine co-driving switching in high-speed operation area based on combination game

doi:10.3969/j.issn.1674-8484.2025.03.015

Abstract

Abstract:

To effectively mitigate the bottleneck effect induced by mixed traffic flow and enhance road safety, a dynamic combination game model based on Stackelberg game and non-cooperative Nash game was presented for the allocation decision of control rights of man-machine vehicles in the road section of the highway operation area. VISSIM software was employed to establish a micro-hybrid traffic flow simulation scenario for the sections in the operation area, validate the effectiveness of the decision model, and analyze the influence of the model on traffic flow safety and traffic efficiency. The results show that the effectiveness of the proposed decision model exceeds 66%, the average conflict incidence is decreased by 34.15%, and the highest conflict incidence is reduced by 70.77% under low traffic flow. The model significantly enhances the safety of the road section in the operation area and effectively improves the traffic efficiency in 91.67% of driving scenarios. In the future, the model should be further applied and optimized to achieve more efficient traffic safety.

Key words: traffic safety, man-machine co-driving, driving strategy, highway, working area

CLC Number:

U492.8

ZHOU Qianxi, WU Chengcheng, HU Zheng, SHI Liangliang. Strategy decision of man-machine co-driving switching in high-speed operation area based on combination game[J]. Journal of Automotive Safety and Energy, 2025, 16(3): 487-495.

Figures/Tables 9

References 21

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驾驶模式	α_i (i为A或M)		ε
驾驶模式	参数值	P值	参数值	P值
人工驾驶	1.635	0.021	0.572	0.492
自动驾驶	2.474	0.001	-0.389	0.642

驾驶模式	α_i (i为A或M)		ε
驾驶模式	参数值	P值	参数值	P值
人工驾驶	1.635	0.021	0.572	0.492
自动驾驶	2.474	0.001	-0.389	0.642

驾驶人疲劳状态	Nash均衡解存/否	收益函数均衡值	结果
不疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} \bar{h}_{\mathrm{tm}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sm}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{1 \mathrm{n}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\mathrm{max}} t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
不疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式
轻微疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} \overline{h_{\mathrm{tn}}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sn}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{\mathrm{ln}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\max } t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
轻微疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式
严重疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} h_{\mathrm{tn}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sn}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{1 \mathrm{n}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\mathrm{max}} t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
严重疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式

驾驶人疲劳状态	Nash均衡解存/否	收益函数均衡值	结果
不疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} \bar{h}_{\mathrm{tm}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sm}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{1 \mathrm{n}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\mathrm{max}} t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
不疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式
轻微疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} \overline{h_{\mathrm{tn}}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sn}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{\mathrm{ln}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\max } t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
轻微疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式
严重疲劳	存在	$\pi_{i}^{*}=\frac{2.474 \beta_{\mathrm{A}} h_{\mathrm{tn}} f_{1 \mathrm{w}} f_{2 \mathrm{w}} f_{3 \mathrm{w}} N_{\mathrm{sn}} d_{\mathrm{n}}}{n \overline{h_{\mathrm{tw}}} f_{1 \mathrm{n}} f_{2 \mathrm{n}} f_{3 \mathrm{n}} N_{\mathrm{sw}} v_{\mathrm{max}} t} \forall i \in\{\mathrm{~A}, \mathrm{M}\}$	人机共驾车辆保持自动驾驶模式通过高速公路作业区路段
严重疲劳	不存在	式(16)不成立	根据式(16)中数值更大一方决策出驾驶人未处于疲劳状态时，车辆的驾驶模式

疲劳状态等级	间隙时间 / s	P_w / %
1级	0.9	0
2级	0.8	8.16
3级	0.7	16.72