Relational model of driver fatigue and vehicle riding trail

Abstract

The invention relates to a relation model between driver fatigue and vehicle driving track, and belongs to the field of transportation. Aiming at fatigue driving early warning application background, by simulating a driving fatigue sampling test of a human-vehicle-road (environment) system in a constructed semi-physical virtual traffic environment, adopting percentage of delta waves and theta waves in facial expression and brain waves of a driver as a standard for judging fatigue degree of the driver, and adopting a method combining time domain analysis and mathematical statistics analysis, the invention researches and determines periodic decreasing driving fatigue preliminary early warning rules of the track of a right front wheel of a vehicle from a right lane line and driving fatigue judgment limit of offset variance of the lane line, can judge fatigue characteristics or moderate fatigue state of the driver, and also researches and determines serious fatigue driving warning rules of abnormal vehicle lane changing. A driving fatigue recognition and early warning system based on the vehicle running track can be established by the invention.

Description

technical field [0001] The invention belongs to the field of traffic and transportation. Aiming at the application background of fatigue driving early warning, it finds the relationship between vehicle driving trajectory and driving fatigue degree through experiments, and provides quantitative basis for further establishing driving fatigue recognition and early warning based on vehicle driving trajectory, and provides traffic safety management. system solutions. Background technique [0002] With the rapid increase of vehicle ownership, the number of traffic accidents remains high, especially in low- and middle-income countries. Traffic safety has attracted the attention of governments and societies around the world. Studies have shown that traffic safety is affected by many factors. Experts at home and abroad have concluded through statistics and research that about 80% of traffic accidents are caused by human factors, and most road traffic accidents are caused by people (m...

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Problems solved by technology

But so far there is no recognized quantitative analysis method, and there is eve

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