基于CIDAS事故数据的路口乘用车-两轮车测试场景研究

doi:10.19562/j.chinasae.qcgc.2023.08.012

Abstract

Abstract:

The existing research on two-wheeler accident scenarios does not distinguish the accident location， so the extraction of two-wheeler accident scenarios at the intersection is far from enough. Therefore， this paper conducts a cluster analysis on 1 239 cases of intersection accidents involving passenger vehicles and two-wheelers from the CIDAS database， and extracts 10 typical two-wheeler accident scenarios at intersections. For the group of strongly correlated variables， the single-layer clustering and double-layer clustering methods are compared， and it is found that the double-layer clustering method has better performance in sample division and interpretation of results. The clustering results are analyzed from the perspective of scenario frequency and injury risk， and the correlation between velocity and scenario injury risk index is further explored. Through the analysis of accident causes， some characteristics scenarios are identified， such as failure to give way， two-wheeler running in the opposite direction， traffic light conflict （including jumping the red light and traffic light switching gap） and visual obstruction. The two-wheeler accident scenarios extracted in this paper can provide a reference basis for the test of intelligent vehicles and active safety systems.

Key words: accident scenarios, passenger car-two-wheeler accident, cluster analysis, intelligent vehicle testing, injury risk

Lin Hu,Gen Li,Fang Wang,Miao Lin,Ning Wu. Research on Test Scenarios of Passenger Cars and Two-Wheelers at Intersections Based on CIDAS Accident Data[J].Automotive Engineering, 2023, 45(8): 1417-1427.

Figures/Tables 12

References 32

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变量编码	描述	取值	选取原因
Re_pos	路口两轮车对乘用车的相对位置	RP0	相对位置、速度大小、运动状态及相对速度方向用于确定预碰撞初始状态。此外，参与方的运动状态、速度和形态特征会影响测试时对两轮车的目标识别和跟踪。
		RP1
		RP2
		RP3
		RP4
		RP5
		RP6
		RP7
Motion_V	乘用车运动状态	直行
		左转
		右转
Motion_T	两轮车运动状态	直行
		左转
		右转
Re_dir	参与方相对速度方向	同向
		反向
		相互垂直
Velocity_V	乘用车速度	常数
Velocity_T	两轮车速度	常数
T_Type	两轮车类型	自行车
		电动两轮车
		两轮摩托车
Time	时间	白天	外部环境条件影响环境感知系统，本文中两轮车测试场景提取的研究须考虑这些极端情况。
Time	时间	夜晚
Weather	天气	下雨
Weather	天气	无雨
Visual_ obstruction	车外视野障碍	有
Visual_ obstruction	车外视野障碍	无
Road_type	路口类型	T字路口	道路状况影响测试车行为决策。
Road_type	路口类型	十字路口
Traffic_light	交通灯装配情况	有
Traffic_light	交通灯装配情况	无

变量字段	取值	簇群
变量字段	取值	S0	S1	S2	S3	S4	S5	S6	S7	S8	总计
T_type	自行车	12	29	14	13	1	9	17	3	9	107
	电动两轮车	130	102	54	11	72	84	98	80	91	722
	两轮摩托车	27	48	15	118	20	39	58	62	23	410
Road_type	T字路口	149	74	59	102	43	43	87	111	25	693
Road_type	十字路口	20	105	24	40	50	89	86	34	98	546
Time	夜晚	25	29	17	105	20	132	0	30	0	358
Time	白天	144	150	66	37	73	0	173	115	123	881
Re_pos	RP0	1	4	3	12	1	3	0	0	0	24
	RP1	0	0	0	4	0	3	0	0	0	7
	RP2	36	0	3	21	22	103	173	0	123	481
	RP3	102	175	1	4	0	23	0	0	0	305
	RP4	1	0	24	87	62	0	0	0	0	174
	RP5	0	0	0	14	4	0	0	7	0	25
	RP6	29	0	52	0	4	0	0	0	0	85
	RP7	0	0	0	0	0	0	0	138	0	138
Motion_V	直行	0	179	79	19	13	106	119	0	84	599
	左转	9	0	0	121	74	22	54	7	18	305
	右转	160	0	4	2	6	4	0	138	21	335
Motion_T	直行	163	159	0	125	76	114	160	145	114	1 056
	左转	4	16	77	15	16	13	7	0	7	155
	右转	2	4	6	2	1	5	6	0	2	25
Re_dir	同向	2	0	63	23	6	6	1	145	0	246
	反向	30	4	20	106	87	3	0	0	0	250
	垂直	137	175	0	13	0	123	172	0	123	743
Weather	无雨	149	160	78	135	83	116	156	135	110	1 122
Weather	有雨	20	19	5	7	10	16	17	10	13	117
Trafic_light	无	153	130	67	118	24	43	173	111	0	819
Trafic_light	有	16	49	16	24	69	89	0	34	123	420
Visual_obstruction	无	143	144	78	130	80	122	130	136	104	1 067
Visual_obstruction	有	26	35	5	12	13	10	43	9	19	172
总计		169	179	83	142	93	132	173	145	123	1 239

变量字段	取值	簇群
变量字段	取值	0	1	2	3	4	5	总计
Re_pos	RP0	11	0	1	0	4	8	24
	RP1	5	0	2	0	0	0	7
	RP2	344	0	1	136	0	120	601
	RP3	0	301	2	0	2	0	305
	RP4	0	0	0	0	54	0	54
	RP5	0	0	25	0	0	0	25
	RP6	2	0	32	0	51	0	85
	RP7	0	0	138	0	0	0	138
Motion_V	直行	301	194	0	0	104	0	599
	左转	0	16	27	136	2	128	309
	右转	61	91	174	0	5	0	331
Motion_T	直行	333	274	198	125	0	126	1 056
	左转	23	21	0	5	105	1	155
	右转	6	6	3	6	6	1	28
Re_dir	同向	5	0	168	10	62	1	246
	反向	12	0	33	29	49	127	250
	垂直	345	301	0	97	0	0	743
总计		362	301	201	136	111	128	1 239

变量字段	取值	簇群
变量字段	取值	J0	J1	J2	J3	J4	C0	C1	C2	C3	总计
T_type	自行车	28	11	8	11	5	24	5	15	0	107
	电动两轮车	183	11	69	54	78	110	65	152	0	722
	两轮摩托车	21	109	27	17	61	0	39	45	91	410
Time	夜晚	32	116	22	11	18	27	109	0	23	358
Time	白天	200	15	82	71	126	107	0	212	68	881
Pre_scenario	P0	0	17	104	0	0	63	48	89	41	362
	P1	154	11	0	0	0	44	19	49	24	301
	P 2	0	17	0	0	144	3	8	24	5	201
	P 3	0	13	0	82	0	11	7	20	3	136
	P 4	57	16	0	0	0	12	8	16	2	111
	P 5	21	57	0	0	0	1	19	14	16	128
Weather	无雨	206	121	98	72	134	121	99	190	81	1 122
Weather	有雨	26	10	6	10	10	13	10	22	10	117
Trafic_light	无	199	111	84	68	132	134	0	0	91	819
Trafic_light	有	33	20	20	14	12	0	109	212	0	420
Visual_ obstruction	无	207	120	87	69	130	94	100	184	76	1 067
Visual_ obstruction	有	25	11	17	13	14	40	9	28	15	172
总计		232	131	104	82	144	134	109	212	91	1 239

场景编码	致伤风险指数	文字描述
J0	0.447	白天在无红绿灯的T字路口，一辆直行/右转的乘用车与来自右侧逆行的电动两轮车相撞（v₁=20-40 km/h、v₂=17-22 km/h）。
J1	0.463	夜晚在无红绿灯的T字路口，一辆左转的乘用车与对向直行两轮摩托车相撞（v₁=20-38 km/h、v₂=20-40 km/h）。
J2	0.402	白天在无红绿灯的T字路口，一辆直行乘用车与前方从左横过马路的电动两轮车相撞（v₁=20-40 km/h、v₂=16-27 km/h）。
J3	0.39	白天在无红绿灯的T字路口，一辆左转乘用车与左方直行电动两轮车相撞（v₁=18-35 km/h、v₂=17-30 km/h）。
J4	0.377	白天在无红绿灯的T字路口，右转乘用车与右后方直行两轮电动车/摩托车发生追尾（v₁=15-30 km/h、v₂=20-30 km/h）。
C0-1	0.41	白天在无红绿灯的十字路口，直行乘用车由于视野障碍与左侧直行电动两轮车相撞（v₁=20-40 km/h、v₂=10-23 km/h）。
C0-2	0.41	白天在无红绿灯的十字路口，一辆直行/右转的乘用车与右侧逆行的电动两轮车相撞（v₁=20-40 km/h、v₂=10-23 km/h）。
C1	0.474	夜晚在有红绿灯的十字路口，直行乘用车与左侧直行两轮电动车/摩托车垂直相撞（v₁=23-42 km/h、v₂=20-30 km/h）。
C2	0.443	白天在有红绿灯的十字路口，直行乘用车与左侧直行两轮电动车垂直相撞（v₁=20-40 km/h、v₂=15-30 km/h）。
C3	0.495	白天在无红绿灯的十字路口，直行乘用车与左侧直行两轮摩托车垂直相撞（v₁=20-40 km/h、v₂=25-40 km/h）。

Research on Test Scenarios of Passenger Cars and Two-Wheelers at Intersections Based on CIDAS Accident Data

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