Driver fatigue monitoring method based on multivariate information fusion

Abstract

The invention discloses a driver fatigue monitoring device based on multivariate information fusion and a monitoring method thereof. The device comprises a digital signal processor, a camera head with a filter, a rectangular ultrared LED light source module mounted on a car windshield, a speaker module and a sensor module comprising an angular sensor and a pressure sensor, wherein the camera head, the rectangular ultrared LED light source module, the speaker module and the sensor module are respectively connected with the digital signal processor. The monitoring method comprises four procedures, namely eye characteristic identification, view line track, driving activity monitoring and fatigue characteristic judgment which merges the fatigue judgment results of the eye characteristic identification, the view line track and the driving activity monitoring to accurately judge the fatigue states of a driver. The invention utilizes an information merging technology to further develop and improve a fatigue driving detection technology, can objectively, rapidly and accurately judge the fatigue state of the driver in real time and avoids traffic accidents caused by fatigue driving.

Description

technical field [0001] The invention belongs to the application field of digital image signal processing and the application field of sensors, and in particular relates to a driver fatigue monitoring device and a monitoring method based on multivariate information fusion. Background technique [0002] With the popularity of automobile consumption, traffic safety has become the focus of restricting the harmonious development of society. The increase in the traffic accident rate caused by driver fatigue has become a hot spot of general concern in the society. Drivers who drive with fatigue have a significant decline in the ability to observe, recognize and control the vehicle, which seriously threatens their own safety and the safety of others. life. [0003] According to research, the number of deaths caused by traffic accidents in the world has exceeded 600,000 every year, and the direct economic losses caused are about 12.5 billion US dollars. Although my country's car ow...

AI Technical Summary

Problems solved by technology

However, in practical application, this method still has many problems: ① the PERCLOS of drivers with different physiques and living habits is very different, so its misjudgment rate is relatively high; ② it is a multiple non- Strict object tracking, changes in lighting conditions in the car and head movement can lead to inaccurate or even failed predictions; ③ When the head is not facing the camera, eye features cannot be recognized; ④ PERCLOS detection cannot be performed when the driver is wearing sunglasses

But in practice, a single detection method cannot be perfect, and there is a certain gap between the accuracy and the ideal state

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