A driver fatigue state detection and reminder method based on multi-source data

Abstract

The invention discloses a driver fatigue state detection and reminder method based on multi-source data. The wearable device and the mobile phone APP collect the driver's sleep status for a certain period of time before the trip, combined with the driver's eye movement data collected by the in-vehicle image collection device, the manual data collected by the sensing device on the steering wheel and the gear position, and the speed change and Lane deviation, comprehensively judge whether the driver is in a fatigue driving state. Based on the physiological data and driving data of the driver's previous n trips, a personal database is established to determine the threshold for fatigue judgment, so as to reduce misjudgments caused by differences in individual drivers and habits. According to the judged driver's fatigue degree, it will give auditory and tactile stimulation reminders respectively, and limit the speed of the vehicle if necessary to avoid dangerous consequences due to fatigue driving.

Description

technical field [0001] The invention belongs to the technical field of traffic engineering active safety, and in particular relates to a driver fatigue state detection and reminder method based on multi-source data. Background technique [0002] With the continuous improvement of the social and economic level and the people's demand for a better life, the development of the transportation industry is changing with each passing day. While providing people with many conveniences, the problem of traffic safety has become increasingly prominent. Hundreds of thousands of people die in traffic accidents worldwide every year. . If the driver is in a state of fatigue during the trip, his reaction speed and operation accuracy will be significantly reduced. The detection and appropriate treatment of driving fatigue can effectively reduce the traffic accidents caused by fatigue driving. [0003] The existing fatigue driving detection technology mainly counts the driver's eye opening ...

AI Technical Summary

Problems solved by technology

[0003] The existing fatigue driving detection technology mainly counts the driver's eye opening and closing time through the eye tracker, or monitors the driver's ECG or EEG signals through sensors that touch the skin and medical sensors, and directly judges fatigue and fatigue with a preset threshold. No, the individual differences of each driver are neglected, and wearable devices can easily cause the driver's physical discomfort, which often affects the monitoring results; some technologies use the driver's sleep duration the previous night as a criterion for judging whether the driver is fatigued or not. Reference basis, but requires manual input from the driver, and the accuracy and reliability need to be improved

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