A Remote Fatigue Driving Detection System for Ship Supervision based on Physiological Response Features

Abstract

Fatigue driving is one of the main influential factors causing maritime accidents, traditional physiological signal detection method has disadvantages such as poor stability and practicability, it has great individual differences and always interferes with the driver operation. This paper proposes a remote fatigue driving detection system based on physiological response features. By fusing different physiological response features such as head posture and eye closure, a fatigue detection model is constructed. As a supplement to single EAR detection for reducing the missed retrieval of eye closure behavior, Single Shot Multi Box Detector is applied to improve the accuracy and robustness of the system. The PERCLOS value is approximately solved by the number of frames with eye closure, and the abnormal head posture angle and the P80 standard have been used to evaluate the fatigue state. Experimental result shows that the detection accuracy has reached 96.9548%, it could meet the demand of ship supervision for driving behavior and fatigue detection which has prosperous application value in seafarers' training and maritime management fields.