LSTM을 이용한 HILS 데이터 판정 자동화 모델 개발에 대한 연구

Abstract

Due to the advancement of autonomous driving technology and the paradigm shift toward electric vehicle, the functions of vehicle have become diverse and complex. For effective function development and verification, car manufacturers are developing functions using the HILS system, but the complexity and diversity of functions make repeated tests inevitable. As a result, human resources are consumed in analyzing numerous test data and determining results. To overcome this problem, This paper proposed an automation model for determining HILS data using LSTM network, one of artificial networks. For model training and verification, we used 2,175 multivariate time series HILS data. Trained model classify testcase number of input data and determine Pass/Fail of input data. The performance of the proposed model was validated by performance index(accuracy, precision, recall, F1-score).