Detecting of driver's drowsiness using multiwavelet packet energy spectrum

Driver drowsiness/fatigue is an important cause of combination-unit truck crashes. The purpose of this study is to detect drowsiness in drivers unobtrusively to prevent accidents and to improve safety on the highways. This paper is the culmination of previous work to determine if steering behavior could be used to unobtrusively detect driver fatigue. In order to investigate the relationship of driver fatigue with steering wheel motion, a fatigue driving model was established. The results of computer simulation demonstrate that the information of driver fatigue hide in steering wheel motion. In order to extract state information contained in it, a multiple scaling functions based multi-wavelet algorithm was proposed which can represent the fatigues characteristic signal and the fatigue characteristic library was be built by using multi wavelet frequency band energy which can represent the fatigue feature of a driver. Finally the paper propose a method of detecting the fatigue driving state by using Support Vector Machines (SVM) which provide the theoretical basis of the development of simple practical driving fatigue monitoring devices.