Safety Assessment and a Parametric Study of Forward Collision-Avoidance Assist Based on Real-World Crash Simulations

Table 7

Regression analysis results: (a) crash model, (b) AEB model, (c) energy model, and (d) injury model.

Regressors	Crash model^1			AEB model^1			Energy model^2			Injury model^2
	β	SE	Sig. flag	β	SE	Sig. flag	β	SE	Sig. flag	β	SE	Sig. flag
Intercept	−3.156	0.253		−3.435	0.340		−162420.49	10122.17		−12.373	1.500
Detection range	−0.049	0.001		−0.029	0.001		−729.29	38.58		−0.073	0.006
Driver reaction time	2.651	0.082		2.743	0.117		44706.31	2944.23		3.737	0.436
Safety margin	−0.096	0.008		−0.133	0.010		−1950.66	326.48		−0.197	0.048
Road friction	−0.163	0.296	ns	2.894	0.399		−595.93	11923.83	ns	−2.399	1.768		ns
Br_inp1	−1.463	0.063		0.672	0.077		−35248.83	2437.02		−3.339	0.361
Subject vehicle’s speed	0.065	0.001		0.069	0.002		4490.73	32.86		0.409	0.005
Leading vehicle’s speed	−0.001	0.002	Ns	0.023	0.003		−1512.25	78.43		−0.133	0.011
Br_L	0.327	0.024		0.318	0.032		12438.63	923.16		1.139	0.137
ADASAL_P	2.311	0.083		2.003	0.104		40057.07	3063.87		6.365	0.454
ADASAL_TTC	0.599	0.080		−0.571	0.077		9267.35	3064.09		0.714	0.454		Ns
ADASNo_AEB	5.167	0.107		−	−	−	106315.14	3063.87		8.324	0.454
	n: 14,185; df: 14,174			n: 10,637; df: 10,627			n: 14,185; df: 14,174			n: 14,185; df: 14,174
	R2 = 0.556;			R2 = 0.432;			R2 = 0.605;			R2 = 0.366;

Logistic regression modelMultiple linear regression model. Significance codes: P ≤ 0.05: ;  ≤ 0.01: ;  ≤ 0.001: ;  > 0.05: ns.