| 제목 |
인공 신경망 기반 오버스티어 판단 알고리즘 개발 |
| 분야 |
차량동역학 및 제어 |
| 언어 |
Korean |
| 저자 |
강성욱(한국기술교육대학교), 김민지(한국기술교육대학교), 이요셉(한국기술교육대학교), 유승한(한국기술교육대학교) |
| Key Words |
Artificial neural network(인공 신경망), Unbalanced data(불균형 데이터), Prediction(예측), Oversteer(오버스티어), Experimental validation(실험적 검증) |
| 초록 |
As the development of control systems used to improve vehicle driving stability becomes more advanced, determining the intervention time of the control logic has become increasingly important. Oversteer is one of the critical factors in determining the lateral stability of a vehicle. Therefore, not only autonomous vehicles, but all vehicles require accurate predictions and judgments for oversteer to ensure driving safety. In this paper, a neural network-based artificial intelligence methodology was used to predict the presence or absence of oversteer. While previous research has been painstakingly conducted with complex judgment conditions and lookup tables, the oversteer decision model based on artificial neural networks of this paper can save time and cost because it can determine whether oversteer occurs without having to consider different individual variables. This model has been validated by using real vehicle experimental data under different driving scenarios. |
| 원문(PDF) |
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