Experimental study of fatigue degree quantification for multi-feature fusion identification |
| |
| Institution: | Sun Wei , Zhu Jiandong , Zhang Xiaorui, He Jun , Zhang Weigong ( School of Information and Control, Nanjing University of Information Science ＆ Technology, Nanjing 210044, P. R. China;School of Electronic and Information Engineering, Nanjing University of Information Science ＆ Technology, Nanjing 210044, P. R. China; School of Instrument Science and Engineering, Southeast University, Nanjing 210096, P. R. China) |
| |
| Abstract: | A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters. |
| |
| Keywords: | fatigue driving fatigue degree quantification fusion identification experimental study |
| 本文献已被 CNKI 维普 等数据库收录！ |
|
