
•
36 actual normal window waveforms used for the evaluation have been predicted as normal, whereas four
have been classified as bumpy.
•
18 actual bumpy window waveforms used for the evaluation have been predicted as bumpy (no miss
classifications).
•
Only one actual skid window waveform has been recognized as skid, whereas three have been confused
with bumpy.
Figure 11.
Confusion matrix
The LSTM RNN accuracy for the AI-car sensing node is about 93%. The miss classification for the skid state
impact the calculated accuracy value, due to the very low number of window waveforms used for training (only
four).
Despite the above considerations, we consider the accuracy value acceptable and defer a new accuracy
calculation for the skid state to the field tests to perform on the sedan.
UM3053
AI-car sensing node life cycle
UM3053
-
Rev 1
page 13/39