Research on transient driving risk vector modeling method under strong constraints of traffic regulations

doi:10.3969/j.issn.1674-8484.2024.05.015

Abstract

Abstract:

To mitigate or alleviate the occurrence of serious accidents where a preceding vehicle stops to yield at a traffic light intersection and was rear-ended by an out-of-control vehicle, a vector field modeling method for vehicle risk was proposed based on the fundamental model of driving risk field force established in the previous studies. An intersection scenario without traffic signals was designed and the safety simulations was conducted under six driving conditions. A dangerous scenario was developed, where a vehicle at a traffic light intersection was at risk of being rear-ended by an out-of-control following vehicle; then, four evasive maneuvers (going straight, turning left, turning right, and making a U-turn) was analyzed without considering road traffic regulations; finally, the force distribution of driving risks across twelve conditions were compared and analyzed. The results show that the proposed model can effectively identify driving risks. The evasive maneuver of the vehicle making a U-turn into the opposite lane is the most optimal, reducing overall risk by 67.41% when the speed is 3 m/s.

Key words: autonomous driving, driving risk, vector modeling, driving safety field

CLC Number:

U461.91

ZHENG Xunjia, JIANG Junhao, LI Huilan, CHEN Xing, LIU Hui, WANG Jianqiang, GAO Jianjie. Research on transient driving risk vector modeling method under strong constraints of traffic regulations[J]. Journal of Automotive Safety and Energy, 2024, 15(5): 774-782.

Figures/Tables 13

References 21

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序号	场景	v_i / (m·s^-1)	F_ji / kN	F_j1i / kN	F_j2i / kN	F_j3i / kN	风险降低率/ %
1	初始	[0,0]	6.411	0.469	0	5.942	—
2	直行	[0,1]	6.499	1.236	0	5.363	-1.37
3		[0,2]	6.892	2.079	0	4.813	-7.50
4		[0,3]	6.823	2.403	0.125	4.293	-6.40
5	左转	[-6/，7/]	5.860	0.984	0	4.875	8.60
6		[-12/，14/]	4.960	1.734	0	3.227	22.63
7		[-18/，21/]	4.511	2.581	0.055	1.874	29.65
8	右转	[2/，3/]	5.953	0.962	0	4.991	7.15
9		[4/，6/]	5.280	1.658	0	3.522	19.21
10		[6/，9/]	4.246	2.057	0	2.188	33.78
11	掉头	[-1,0]	5.149	0.517	0	4.632	19.68
12		[-2,0]	3.263	0.568	0	2.695	49.11
13		[-3,0]	2.089	0.620	0	1.469	67.41

序号	场景	v_i / (m·s^-1)	F_ji / kN	F_j1i / kN	F_j2i / kN	F_j3i / kN	风险降低率/ %
1	初始	[0,0]	6.411	0.469	0	5.942	—
2	直行	[0,1]	6.499	1.236	0	5.363	-1.37
3		[0,2]	6.892	2.079	0	4.813	-7.50
4		[0,3]	6.823	2.403	0.125	4.293	-6.40
5	左转	[-6/，7/]	5.860	0.984	0	4.875	8.60
6		[-12/，14/]	4.960	1.734	0	3.227	22.63
7		[-18/，21/]	4.511	2.581	0.055	1.874	29.65
8	右转	[2/，3/]	5.953	0.962	0	4.991	7.15
9		[4/，6/]	5.280	1.658	0	3.522	19.21
10		[6/，9/]	4.246	2.057	0	2.188	33.78
11	掉头	[-1,0]	5.149	0.517	0	4.632	19.68
12		[-2,0]	3.263	0.568	0	2.695	49.11
13		[-3,0]	2.089	0.620	0	1.469	67.41