Stacking-Based Ensemble Learning Method for the Recognition of the Pedestrian Crossing Intention

Table 3

Model evaluation result at 0 s before crossing the zebra crossing.

Algorithm	Accuracy (%)	WSI			WWI			SWI
		Pr (%)	Re (%)	F1 (%)	Pr (%)	Re (%)	F1 (%)	Pr (%)	Re (%)	F1 (%)
SVM	90.08	88.24	89.29	88.76	89.63	89.63	89.63	92.50	91.36	91.93
RF	92.12	90.59	91.67	91.12	92.07	92.07	92.07	93.75	92.59	93.17
LSTM	93.54	91.76	93.41	92.58	93.9	93.33	93.62	95.00	93.83	94.41
AT-Bi-LSTM	96.15	95.29	95.86	95.58	96.34	95.76	96.05	96.88	96.88	96.88
Stacking	98.79	98.24	98.82	98.53	98.78	98.78	98.78	99.38	98.76	99.07

Note. Pr represents precision, Re represents recall, and F1 represents F1 scores.