自动驾驶汽车接管模式与事故严重程度关联性分析

doi:10.13229/j.cnki.jdxbgxb.20250060

Abstract

Abstract:

In order to investigate the factors influencing the severity of injury in self-driving car accidents， a structural equation model considering mediating effects was constructd to analyze the correlation between the takeover mode of self-driving cars and the severity of accidents. Using the self-driving car accident data in AVOID dataset， 17 influencing factors were selected from four aspects： vehicle characteristics， weather characteristics， road characteristics and collision conditions， and the mediating effect and factor structure analysis were used to explore the influence of each factor on the severity of self-driving accidents. The results show that road type can significantly reduce the severity of self-driving car accidents. Road condition， weather-cloudy， weather-rain， collision-left rear and lighting-daylight indirectly affect the severity of self-driving car accidents through the mediating effect. Among them， road condition can significantly reduce the severity of traffic accidents. Weather-rain significantly increases the severity of traffic accidents of self-driving cars. The takeover mode of the self-driving car when it is involved in a traffic accident has a significant negative effect on accident severity and the two have a complex correlation.

Key words: engineering of communications and transportation system, accident severity, structural equation modelling, self-driving cars, car takeover, mediating effects

CLC Number:

U491

Yi-yong PAN,Sai-sai YANG. Analysis of correlation between self⁃driving car takeover mode and accident severity[J].Journal of Jilin University(Engineering and Technology Edition), 2026, 56(8): 2077-2083.

Figures/Tables 7

Table 1

Table 2

Structural equation model fitting metrics"

拟合

指标

χ 2

χ 2 / d f

P值

TLI

RMR

AGFI

参考值

>0.05

>1；<3

<0.05

>0.9

<0.05

>0.9

指标值

18.941

2.706

0.008

0.592

0.022

0.922

Table 2

Table 3

Table 4

Fig.1

Fig.2

Table 5

References 16

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分类	自变量	自变量描述	频数
车辆特性	汽车品牌	本田	11
		通用	28
		福特	31
		本田	47
		捷豹	110
		斯巴鲁	21
		特斯拉	38
		丰田	24
		其他（宝马/奥迪/奔驰/现代/凯迪拉克/雷克萨斯）	82
	接管模式	ADS模式	194
		ADAS模式	86
		人工接管	112
	车型年份	2015~2016	28
		2017~2018	27
		2019~2020	119
		2021~2022	200
		其他（2023/未知）	8
	自动系统使用年份	少于2年	228
		2~5年	122
		5年以上	35
		其他（未知）	7
天气特性	雨	是	14
	雨	否	377
	多云	是	27
	多云	否	365
道路特性	道路类型	高速公路	93
		交叉路口	135
		街道	102
		其他	62
	路面状况	干燥	369
	路面状况	湿润	23
	道路照明	白天	278
		黄昏和黎明	15
		夜晚	99
碰撞状况	碰撞区域（前方）	是	73
	碰撞区域（前方）	否	319
	碰撞区域（左前方）	是	68
	碰撞区域（左前方）	否	324
	碰撞区域（右前方）	是	69
	碰撞区域（右前方）	否	323
	碰撞区域（后方）	是	98
	碰撞区域（后方）	否	294
	碰撞区域（左后方）	是	80
	碰撞区域（左后方）	否	312
	碰撞区域（右后方）	是	89
	碰撞区域（右后方）	否	303
	碰撞区域（左方）	是	31
	碰撞区域（左方）	否	361
	碰撞区域（右方）	是	25
	碰撞区域（右方）	否	367

路径	估计值	SE	95% BCa 置信区间	P值
接管模式→路面状况	0.093	0.057	［0.040， 0.281］	0.002
接管模式→天气（多云）	0.128	0.051	［0.080， 0.301］	0.000
接管模式→天气（雨）	0.006	0.088	［-0.178， 0.189］	0.869
接管模式→碰撞（左后方）	0.105	0.053	［0.006， 0.213］	0.026
接管模式→照明（白天）	-0.161	0.045	［-0.239， -0.058］	0.000
事故严重程度→接管模式	-0.119	0.043	［-0.179， -0.009］	0.034
事故严重程度→街道	-0.191	0.046	［-0.247， -0.062］	0.001
事故严重程度→交叉路口	-0.246	0.040	［-0.268， -0.103］	0.000

路径	估计值	SE	Z值	P值
接管模式→路面状况	5.296	0.310	17.100	0.000
接管模式→天气（多云）	1.113	0.534	2.087	0.037
接管模式→天气（雨）	－4.384	0.311	－14.095	0.000
接管模式→碰撞（左后方）	0.414	0.195	2.128	0.033
接管模式→照明（白天）	－0.543	0.174	－3.121	0.002
事故严重程度→接管模式	－0.153	0.077	－1.992	0.046
事故严重程度→街道	－0.719	0.226	－3.185	0.001
事故严重程度→交叉路口	－0.775	0.218	－3.551	0.000

变量	ACME		ADE		PM
变量	估计值	P值	估计值	P值	估计值	P值
路面状况	-0.030 1	0.012	0.063 1	0.436	-0.911 8	0.718
天气（多云）	-0.031 8	0.004	0.077 2	0.318	-0.699 0	0.602
天气（雨）	-0.026 4	0.014	0.085 8	0.348	-0.444 8	0.556
碰撞（左后方）	-0.012 8	0.042	-0.088 0	0.020	0.126 9	0.046
照明（白天）	0.017 9	0.010	0.035 1	0.350	0.337 4	0.130
街道	-0.021 2	0.016	-0.065 9	0.074	0.243 7	0.032
交叉路口	0.006 0	0.330	-0.122 2	0.000	-0.051 4	0.330

Analysis of correlation between self⁃driving car takeover mode and accident severity

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