TY  - JOUR
PY  - 2023//
TI  - Development of oversteer prediction algorithm based on artificial neural networks
JO  - Transactions of the Korean Society of Automotive Engineers
A1  - Kang, Sungwook
A1  - Kim, Minji
A1  - Lee, Joseph
A1  - You, Seung-Han
SP  - 667
EP  - 673
VL  - 31
IS  - 9
N2  - 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.<p />  <p>Language: ko</p>
LA  - ko
SN  - 1225-6382
UR  - http://dx.doi.org/10.7467/KSAE.2023.31.9.667
ID  - ref1
ER  -