自动驾驶接管过程中驾驶能力恢复状态对交通流振荡特性的影响

doi:10.13229/j.cnki.jdxbgxb.20230371

摘要/Abstract

摘要：

利用模拟器开展了自动驾驶接管仿真实验，采集了实验过程中的车辆轨迹数据，利用高斯混合模型将接管后的驾驶状态划分为稳定与不稳定，并确定了被试的驾驶能力恢复时间。随后，利用遗传算法标定了驾驶能力恢复阶段与正常手动驾驶阶段的跟驰模型参数，并通过数值仿真技术，研究了不同扰动强度下驾驶能力恢复时长对交通振荡特性的影响规律。结果表明：接管后驾驶人平均需要27.25 s来恢复驾驶能力；驾驶能力恢复阶段的期望加速度与减速度大于正常手动驾驶阶段，而期望速度要小于正常手动驾驶阶段；接管会引起交通振荡，振荡持续时间与驾驶能力恢复时长和扰动强度正相关，而驾驶能力恢复时长对振荡幅度无显著影响；此外，交通振荡在车队传播过程中其振幅和持续时间会被不断放大。

关键词: 交通运输系统工程, 自动驾驶, 驾驶能力恢复状态, 交通振荡, 数值仿真

Abstract:

This study conducted an automated driving takeover test using a driving simulator to collect vehicle trajectory data. Then， participants driving ability recovery time was derived by employing the Gaussian mixture model to classify the driving state as either stable or unstable. Then， the parameters of the intelligent driver car-following model for the driving ability recovery and the norm manual driving state were calibrated using the genetic algorithm. Finally， numerical simulation techniques were employed to explore the impacts of driving ability recovery time on the propagation characteristics of traffic oscillations under various intensities of traffic disturbance. Results indicated that drivers took an average of 27.25 s to recover their driving ability. In the driving ability recovery state， the desired acceleration and deceleration were higher， while the desired speed was lower. Furthermore， the takeover of automated vehicles resulted in traffic oscillation， and the duration was positively linked to the driving ability recovery time and intensity of traffic disturbance. However， the amplitude of traffic oscillation was not significantly affected by the recovery time. Moreover， both the duration and amplitude of oscillation were amplified during its propagation in the simulation fleet.

Key words: transportation system engineering, automated driving, recovery of driving performance, traffic oscillation, numerical simulation

中图分类号:

U471.3

王长帅,徐铖铖,任卫林,彭畅,佟昊. 自动驾驶接管过程中驾驶能力恢复状态对交通流振荡特性的影响[J]. 吉林大学学报(工学版), 2025, 55(1): 150-161.

Chang-shuai WANG,Cheng-cheng XU,Wei-lin REN,Chang PENG,Hao TONG. Impacts of driving ability recovery state on characteristics of traffic oscillation in automated driving takeover process[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(1): 150-161.

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序号	自动驾驶持续时间/s	自动驾驶速度/（m·s^-1）	接管前置时间/s	前车速度 /（m·s^-1）
1	180	22.22	6	18.06
2	60	23.61	6	15.28
3	300	25.00	6	16.67
4	300	22.22	4	15.28
5	180	23.61	4	16.67
6	60	25.00	4	18.06
7	60	22.22	5	16.67
8	300	23.61	5	18.06
9	180	25.00	5	15.28

符号	变量的描述及定义
x₁	每秒内后车的平均纵向速度/（m·s^-1）
x₂	每秒内后车纵向速度的标准差
x₃	每秒内后车的平均纵向加速度/（m·s^-2）
x₄	每秒内后车的平均跟驰距离/m
x₅	每秒内后车跟驰距离的标准差
x₆	每秒内前后车速度差的均值/（m·s^-1）
x₇	每秒内前后车速度差的标准差
x₈	每秒内前后车的平均车头时距/s
x₉	接管后的时间（被试接管车辆的时刻为0时刻）
x₁₀	每秒内后车的平均横向速度/（m·s^-1）
x₁₁	每秒内后车横向速度的标准差
x₁₂	每秒内后车的平均横向加速度/（m·s^-2）
x₁₃	每秒内后车的平均车道偏移量/m
x₁₄	每秒内后车车道偏移量的标准差

参数	驾驶能力恢复阶段	正常手动驾驶阶段
A/（m·s^-2）	1.01	0.45
b/（m·s^-2）	5.21	0.67
v_f /（m·s^-1）	25.52	39.98
s₀/m	9.88	9.37
T/s	1.26	1.73

v_δ /（m·s^-1）	时间/s	减速波/（m·s^-1）	加速波/（m·s^-1）	v_δ /（m·s^-1）	时间/s	减速波/（m·s^-1）	加速波/（m·s^-1）
2.78	20	15.53	2.53	8.33	20	17.74	2.40
2.78	24	15.53	2.58	8.33	24	17.74	2.46
2.78	28	15.53	2.69	8.33	28	17.74	2.49
2.78	32	15.53	2.81	8.33	32	17.74	2.47
2.78	36	15.53	2.96	8.33	36	17.74	2.38
2.78	40	15.53	3.12	8.33	40	17.74	2.28
5.56	20	16.77	0.07	11.11	20	18.32	3.70
5.56	24	16.77	0.15	11.11	24	18.32	3.77
5.56	28	16.77	1.75	11.11	28	18.32	3.76
5.56	32	16.77	2.00	11.11	32	18.32	3.65
5.56	36	16.77	2.15	11.11	36	18.32	3.51
5.56	40	16.77	2.24	11.11	40	18.32	3.39

变量名	振荡持续时间			振荡幅度
变量名	参数值	标准差	P值	参数值	标准差	P值
调整后的R²	0.951			0.959
扰动强度	13.231	0.117	<0.001	3.167	0.019	<0.001
驾驶能力恢复时间	0.898	0.053	<0.001	-0.015	0.009	0.08
ID	2.548	0.025	<0.001	0.075	0.004	<0.001
常数项	-23.728	1.941	<0.001	-6.864	0.316	<0.001