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Fatigue driving state detecting system and method based on decision-making level data integration

A fatigue driving and data fusion technology, applied in character and pattern recognition, diagnostic recording/measurement, medical science, etc., can solve the problems of low detection accuracy, large environmental factors, high hardware cost, etc., to improve detection accuracy The effect of high rate and detection accuracy

Active Publication Date: 2015-09-30
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0007] In short, the current research results generally have defects such as low detection accuracy, high hardware cost, difficult to wear equipment, and greater influence by environmental factors.

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  • Fatigue driving state detecting system and method based on decision-making level data integration
  • Fatigue driving state detecting system and method based on decision-making level data integration
  • Fatigue driving state detecting system and method based on decision-making level data integration

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Embodiment Construction

[0048] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0049] The fatigue driving state detection method based on the decision-making level data fusion of the present invention comprehensively utilizes the indirect information of the motion acceleration of the steering wheel and the direct pulse information of the driver, which can effectively improve the detection accuracy of the fatigue driving state: the acceleration sensor is used to collect the motion acceleration data of the steering wheel, The weighted moving average method is applied to these raw data for smoothing, and based on the theory of 4s non-movement of the steering wheel, the detection result of the fatigue driving state is preliminarily judged; at the same time, the pulse sensor is used to collect the pulse data of the driver during driving, and the driving force is analyzed and calculated. According to the change of pulse rate of the driver, the thresho...

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Abstract

The invention discloses a fatigue driving state detecting system and method based on decision-making level data integration. The fatigue driving state detecting system firstly uses an acceleration sensor to acquire motion acceleration of a steering wheel, judges motion states of the steering wheel based on dynamic acceleration threshold values, and primarily judges fatigue driving states of a driver based on 4s immobility theory. Detecting error tolerance is improved by setting errors of the steering wheel turning from left to right. Pulse time domain values of the driver can be acquired via a pulse sensor, and physiological states of the driver can be detected based on dynamic pulse threshold values. Integrated detecting results can be obtained by integrating two kinds of detecting results in decision making level. By the fatigue driving state detecting method based on decision-making level data integration, a fatigue driving state detecting prototype system is constructed. Compared with existing methods, the fatigue driving state detecting method based on decision-making level data integration has certain advantages in detection accuracy and perfect performance in response time, time complexity, memory occupation and the like of algorithms.

Description

technical field [0001] The invention relates to a driving state detection method, in particular to a fatigue driving state detection method, which belongs to the cross-technical application field of mobile computing, sensing technology and data fusion. Background technique [0002] Fatigue driving generally refers to the situation in which the driver's control ability is abnormal due to fatigue changes in the body mechanism during driving, which seriously endangers road traffic safety and has become a serious problem facing the world. The report of the National Highway Traffic Safety Administration of the United States shows that traffic accidents caused by driver fatigue driving account for 20%-30% of the total number of traffic accidents. For example, at around 2:31 on August 26, 2012, the driver, Mr. Chen, was driving a sleeper bus and collided with a heavy-duty tank-type semi-trailer train, causing 36 people in the bus to die on the spot; System, GPS) records, the drive...

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Application Information

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IPC IPC(8): G08B21/06A61B5/18G06K9/62
Inventor 徐小龙李硕李涛徐佳李千目章韵
Owner NANJING UNIV OF POSTS & TELECOMM
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