Critical Factors Analysis of Severe Traffic Accidents Based on Bayesian Network in China

Table 8

Risk degree raking of single-vehicle traffic accidents.

Factor variables	Severity analysis result of the number of deaths			Severity analysis result of the number of injuries
	Expectation	Ranking vector	Ranking	Expectation	Ranking vector	Ranking
Overspeed	(15.381, 24.530)	0.1097	8	(15.381, 24.530)	0.1171	6
Commuter bus involved	(17.018, 26.220)	0.1225	6	(17.018, 26.220)	0.1531	1
Straight alignment	(17.008, 26.486)	0.1235	5	(17.008, 26.486)	0.1169	7
Physical separation	(17.885, 27.424)	0.1303	3	(17.885, 27.424)	0.1189	5
Slippery pavement	(17.040, 26.521)	0.1238	4	(17.040, 26.521)	0.1196	4
Night	(18.267, 27.834)	0.1333	2	(18.267, 27.834)	0.1399	2
Poor weather	(18.482, 28.073)	0.1350	1	(18.482, 28.073)	0.1211	3
Poor visibility	(16.803, 26.266)	0.1219	7	(16.803, 26.266)	0.1134	8