基于大腦認(rèn)知分析的駕駛疲勞檢測(cè)與緩解技術(shù)研究
[Abstract]:Driving fatigue is one of the main causes of traffic accidents. Driving fatigue is ubiquitous and harmful. Therefore, research and development of high-performance driver fatigue detection technology, and when necessary to warn the driver of dangerous state intervention, promptly remind the driver to slow down or stop to rest, alleviate driving fatigue to improve. Driving fatigue refers to the monotony of driving environment or long-term excessive intensity driving, the driver due to physical and mental exhaustion caused by excessive physical and mental decline, resulting in sluggish response, stiff movement, perception of the surrounding environment, situation judgment and the ability to control vehicles are different. Based on the above physiological factors of driving fatigue, a hardware-in-the-loop simulation system for vehicle safety driving is established in this paper, which can monitor the driver's driving state in real time and alleviate the driver's fatigue when necessary, so as to provide guarantee for safe driving. The following aspects are discussed: 1. The characteristics of fatigue driving are analyzed by the synchronization of nerve activities in different brain regions. It is found that even very simple cognitive tasks are performed by multiple brain regions. During this period, the synchronization of nerve activities between different brain regions is quite different. The human brain is modeled and the complex brain network is constructed. The changes of driving fatigue are analyzed by changing the important parameters of the brain network. The changes of driving fatigue are analyzed by combining the power spectrum of EEG and the characteristics of EOG. 2. The fatigue driving test of long-distance bus drivers is carried out in China. Long-distance bus is one of the main means of transportation and undertakes important passenger tasks. The normal driving of passenger drivers is related to the safety of passengers'lives and property. Therefore, it is of great significance to analyze the driving fatigue of long-distance bus drivers. After real-time monitoring and acquisition of EEG signals of 10 drivers, a brain network was constructed, and the characteristics of brain network were studied. The driving fatigue characteristics of long-distance bus drivers under real driving environment were analyzed. The results showed that the clustering coefficient and global efficiency of brain network parameters of long-distance bus drivers changed regularly with the deepening of driving fatigue. Taxi occupies a considerable proportion in urban traffic. Therefore, it is of great significance to study the alleviation of taxi driving fatigue for urban traffic safety. In the experiment, eight drivers were selected and their EEG signal characteristics were analyzed to determine the most favorable way to alleviate driving fatigue. The results showed that the taxi drivers chose the rest of free activities outside the vehicle, more importantly. Driving fatigue is a comprehensive physiological fatigue state, including mental fatigue and physical fatigue. According to the theory of traditional Chinese medicine, stimulating the palm of the human body's Laogong acupoint (PC8) can make people wake up and alleviate the symptoms of fatigue. Functional electrical stimulation instrument (KWD-808I) was used to stimulate the Labor Palace acupoint (PC8), and the alleviating effect of electrical stimulation on driving fatigue was analyzed. When holding the steering wheel, the acupoint contacts with the stimulating electrode naturally, and does not need the patch electrode. 5. A hardware-in-the-loop simulation system for vehicle safety driving is established. The system can collect the driver's EEG signals in real time and monitor the changes of driver's fatigue characteristics. If the driver in the loop is fatigued because of driving for a long time, and the driver's cognition of the vehicle is deviated greatly, the driver's action will make the wrong operation to the vehicle's driving. At this time, the system will monitor through the sensor. The driver's mental state, timely determine the driver's mental fatigue, determine whether it is suitable to continue driving instructions to ensure safe driving, eliminate traffic safety risks.
【學(xué)位授予單位】:東北大學(xué)
【學(xué)位級(jí)別】:博士
【學(xué)位授予年份】:2015
【分類(lèi)號(hào)】:U491.254;U463.6
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