Table 1 The summary of the results of the introduced framework.

Models	Factors	AP^a	Statistical weight^b	Norm. weight^c
Model1-NightNet	Nightime	0.885	0.268	0.101
	Daytime	0.885	0.120	0.045
	Dawn_dusk	0.885	0.417	0.157
Model2-GlareNet	Glare	0.883	0.099	0.037
Model3-PrecipitationNet(b)	Clear	0.959	0.117	0.044
	Rain	0.959	0.281	0.106
	Snow	0.959	0.199	0.075
Model4-FogNet	Fog	0.862	0.241	0.091
Model5-SlipNet	Wet surface	0.918	0.241	0.091
Model6-Object_detection	Person	0.75	0.074	0.028
	Bicycle	0.79	0.201	0.076
	Car	0.81	0.089	0.034
	Bus	0.77	0.100	0.038
	Motorbike	0.81	0.368	0.139
	Truck	0.77	0.034	0.013
Model7-Cyclinglane	Cyclinglane	0.91	0.1235	0.047

^aThe average precision calculated for each model on the test sets.
^bThe absolute value of the statistical weight of the second logistic regression model computed based on the coefficient (B) statistics.
^cThe normalised version of the statistical weight is introduced in the previous column.

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