Absolutely dry!! AI intelligent fatigue driving detection technology scheme
In recent years, traffic accidents caused by fatigue driving have been reported frequently and become the “invisible killer” of vehicles. Not drunk driving, not speeding and not fatigue driving… Should be the basic point that every driver with a driver’s license should pay attention to. However, affected by the awareness of “drinking a little wine is not an obstacle, not tired and not sleepy”, many people think that they know the situation best when driving, and are careless, It is often easy to cause accidents. China’s transportation industry is developing rapidly, and the following road traffic accidents also show an upward trend. According to the data of the transportation department, the traffic accidents caused by fatigue driving account for a large proportion, accounting for a larger proportion of major traffic accidents. Fatigue driving has been the main hidden danger of traffic accidents, which has attracted people’s attention, There are also many detection devices for fatigue driving. For example, the prior art provides a method to analyze the driver’s fatigue state through face recognition and pupil monitoring, and make corresponding early warning according to the fatigue situation.
Although the above method can also achieve a certain early warning function to a certain extent, it has the following shortcomings: 1 Face recognition and pupil monitoring belong to image acquisition and analysis. Simple image acquisition and analysis under limited CPU computing unit can not guarantee real-time and accuracy; 2. In the process of pupil monitoring, the accuracy of pupil monitoring is not high due to the complex situation of the driver and the ever-changing ambient light. For example, when drivers wear various glasses, different glasses reflect different ambient light, which often leads to great deviation in the results of pupil monitoring.
Therefore, the fatigue driving monitoring system not only monitors the driver’s face information and pupil information, but also monitors his head movement information and heart rate information, and integrates these information to generate an overall information of the driver’s behavior, which avoids the defect of large error caused by simple face recognition and pupil monitoring in the prior art, and has high monitoring accuracy, It ensures the driving safety of the driver.
The image acquisition module includes a face recognition sub module for collecting face information, a pupil monitoring sub module for monitoring pupil information, and a head motion monitoring sub module for monitoring head movement information. The image acquisition module is used to collect the face information, pupil information Fusing the head movement information to generate first human body image information; A heart rate monitoring module for monitoring heart rate data and generating heart rate signals based on the heart rate data; The central control unit is connected with the image acquisition module and the heart rate monitoring module. The central control unit is used to receive the first human body image information and heart rate signal, and generate a comprehensive driver behavior signal based on the first human body image information and heart rate signal.
The utility model is characterized in that it comprises an image acquisition module, the image acquisition module comprises a face recognition sub module for collecting face information, a pupil monitoring sub module for monitoring pupil information, and a head motion monitoring sub module for monitoring head movement information, and the image acquisition module is used for integrating the face information, pupil information Fusing the head movement information to generate first human body image information; A heart rate monitoring module for monitoring heart rate data and generating heart rate signals based on the heart rate data; The central control unit is connected with the image acquisition module and the heart rate monitoring module. The central control unit is used to receive the first human body image information and heart rate signal, and generate a comprehensive driver behavior signal based on the first human body image information and heart rate signal. 2. The fatigue driving monitoring system according to claim 1, which is characterized in that the image acquisition module further comprises a face micro expression monitoring sub module for monitoring the face micro expression information, and the image acquisition module is also used to fuse the face information, pupil information and head movement information with the face micro expression information to generate second human body image information. 3. The fatigue driving monitoring system according to claim 1, which is characterized in that it further comprises an alarm module, which is connected with the central control unit to send an alarm signal when the comprehensive signal of driver behavior exceeds the fatigue driving threshold. 4. A vehicle, which is characterized in that it comprises the fatigue driving monitoring system according to any one of claims 1-3. 5. The vehicle according to claim 4, which is characterized in that the image acquisition module is arranged on the front windshield of the vehicle and is facing the driver. 6. The vehicle according to claim 4, which is characterized in that the heart rate monitoring module is a heart rate monitoring bracelet, and the heart rate monitoring bracelet is worn on the driver’s wrist. 7. The vehicle according to claim 6, which is characterized in that the central control unit is arranged on the vehicle, and the central control unit is wirelessly connected or wired with the image acquisition module. 8. The vehicle according to claim 6 or 7, which is characterized in that the central control unit is wirelessly connected with the heart rate monitoring module.
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