Simulation Driving Fatigue Physical Characteristics Research And Application

In recent years, with the accelerating rhythm of life, daily life and work offatigue always affects the physical and mental health of the individual. As thetraffic conditions become increasingly crowded, fatigue driving gets more andmore attention. How to effectively reduce fatigue damage, convenient andbecome one of hot topics in the study of the present safe driving. And as themost direct response to drivers’ mental state eye related behavioral research,there are still some short comings. Therefore, research on the behavior ofdriver’s eye fatigue monitoring, to improve personal physical and mentalconditions and reduce the traffic accident harm has certain theoretical andpractical value.Based on the study of the formation mechanism of driving fatigue,considering factors related to fatigue, equipped with simulated driving testenvironment, the driver’s eye during simulated driving behavior data collectedby the eye tracker, and to analyze the experimental data the study. The mainwork is as follows:1.Based on the research of the characteristics of driver fatigue analysis,choose driver eye behavior characteristics as a research method, buildsimulation experiment environment. By taking advantage of eye movementapparatus simulating driving experiment driving human eye movement indexdata acquisition.2.Through the analysis of drive eye behavior index research,based on theanalysis of the pupil diameter data. We put forward the pupil diameter envelopethreshold indicator. Through test statistics and average clustering method, and compared to the original eye movement behaviours related indicators. Know thepupil diameter envelope index can be used to detect the driver’s state.3. To further verify the pupil diameter envelope index on the accuracy ofthe driver fatigue evaluation. Combining multiple features fusion related theoryknowledge, selection of BP neural network model for driver fatigue based onpupil diameter envelope index evaluation method, established the blink of aneye time average index and the pupil diameter envelope index as input elementsof the BP neural network evaluation model, and for training and testing. Verifythe pupil diameter envelope index can be used as a new, more accurate driverfatigue evaluation index.4.Based on driver behavior based on the research of the characteristicindexes of eye, driving fatigue design of early warning system, according to theactual system requirements analysis and the real time and convenience of eyemovement indicators monitoring fatigue driving. Implement driving fatiguemonitoring system based on pupil diameter envelope indicators of interfacedesign, and performance testing of the system.