Study Of The Detection And Alleviation For Driving Fatigue Based On Brain Cognition Analysis

Driving fatigue is one of the main causes of the accident. Driving fatigue is widespread and can bring great harm to us. Therefore, developing a method which can accurately and rapidly detecting driving fatigue state and alleviating fatigue are particularly important. Driving fatigue, caused by monotonous driving for a long time, is a physiological state, with slow actions and low awareness, which can lead to traffic safety trouble. The vehicle safety driving semi-physical simulation system was built. It can real-time monitor the driver's driving state and ease driving fatigue in times fatigue in times of real need. The implications of data analysis are explored in the following discussion.1. The synchronization differences of neural activity between pairs of brain regions were used to analyze the driving fatigue characteristics. The study has found that even in a simple cognitive task, it also needs multiple brain regions to complete together. And there are significant differences of synchronization between pairs of brain regions. In this thesis, the complex brain network was built. And its main parameters were used to analyze the driving fatigue. Combining with the relative power spectrum of electroencephalogram (EEG) signals and electro-oculogram (EOG) signals, the relationship of the different characteristics for driver fatigue was discussed.2. The experiment of driving fatigue test for drivers of coach bus was done. In our country, coach bus is one of the main means of transportation. The safe driving of passenger drivers related to the life property safety of the passengers. Therefore, it is a great significance to give a analysis to drivers' driving fatigue. In the experiment, the subjects drove along the highway from Shenyang to Dandong, China, in a busy traffic situation on a sunny day. A total of 10 healthy subjects had been chosen for this experiment. And the driving fatigue characteristics were analyzed for the drivers. It is shown that the changes of driver fatigue state can be detected effectively by calculating the cluster coefficient C and path length L of brain networks in an actual driving condition.3. The effect differences between the two traditional types of easing driving fatigue were analyzed. For the urban traffic, the taxi occupies a large proportion of vehicles. Therefore, the study of taxi drivers rest is particularly important significance. The survey found that two main types of rest, rest in a car and out a car, can be used when the taxi drivers feel fatigue after long time driving. A total of 8 healthy subjects have been chosen for this experiment. And the driving fatigue characteristics were analyzed for the drivers using the two types of driving fatigue easing. It is shown that the driving fatigue can be better eased when taxi drivers rest out a car comparing rest in a car.4. The experiment for alleviating driving fatigue using transcutaneous acupoints electrical stimulations (TAES) was done. Driving fatigue is a comprehensive physical fatigue state including mental fatigue and physical fatigue. From the view of traditional Chinese medicine (TCM), stimulating the Laogong point (??PC8) is helpful for relieving metal fatigue. In this thesis, the multi-purpose health device (KWD-808I) is used as electrical stimulator. And the analysis for the effect of alleviating driving fatigue using electrical stimulation was done. The results show that the fatigue caused by long-time monotonous driving can be eased after the subjects being given the electrical stimulation. Therefore, it can be concluded that stimulating Laogong point (??PC8) can relieve driver fatigue, which is helpful for improving the safe driving for long time driving. In addition, this method, needs not stick electrodes, is convenient and practical to be used in actual driving situations, which provides a new method for relieving driving fatigue during long time driving.5. The vehicle safety driving, semi-physical simulation system was built. It can real-time monitor the driver's driving state and ease driving fatigue in times of real need. Drivers can adjust their driving behaviors on the basis of data obtained from the road traffic and car dashboard. The drivers may have a big deviation to driving cognitive even make wrong judgments to driving behavior due to driving fatigue. At this time, the system can monitor the driver's driving state and give a decision whether it can be allowed to continue to drive for safe driving.