Experimental method for verification of abnormal driving behavior algorithm model based on 5G communication

Abstract

The invention discloses a verification experiment method based on an abnormal driving behavior algorithm model under 5G communication, including the following steps: driver background segmentation, identification and positioning of the driver's key sub-region image, identification of the driver's behavior state and time, verification analysis and experiment deployment The present invention first designs the driver's background image segmentation algorithm based on the improved Mask-RCNN and segments the driver's background image, then designs based on the improved Yolov3 target detection algorithm and recognizes the driver's key sub-region image after the segmented image, and then Design the CNN-LSTM fusion classification algorithm applied to the recognition scene of abnormal driving behavior and let it recognize the driver's action state and time by inputting three kinds of images. Realize the verification experiment of the algorithm model, which has high practicability, so that the accuracy and speed of the algorithm model are guaranteed.

Description

technical field [0001] The invention relates to the technical field of abnormal driving behavior detection, in particular to a verification experiment method based on an algorithm model of abnormal driving behavior under 5G communication. Background technique [0002] Algorithm research on abnormal behavior detection of drivers belongs to the field of intelligent transportation and is a key technology of intelligent assisted driving. This technology detects abnormal behavior of drivers and issues warnings to avoid traffic accidents, which has important application value and social significance At this stage, the research and development in this field in many countries at home and abroad are limited by the characteristics of abnormal behaviors. For example, there are many types of abnormal behaviors, including driver fatigue behaviors such as closing eyes for a long time, yawning, rubbing eyes, and nodding, and improper driving behaviors. The categories are complex, including...

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Problems solved by technology

[0003] At present, most of the abnormal driver behavior recognition and classification algorithms proposed for driver abnormal behavior detection have not undergone effective and reliable verification analysis and experimental deployment, resulting in the accuracy and speed of the algorithm model cannot be guaranteed, and the comprehensive performance and practicability It cannot be determined, therefore, the present invention proposes a verification experiment method based on the abnormal driving behavior algorithm model under 5G communication to solve the problems existing in the prior art

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