摘要
危险驾驶检测系统主要作用于驾驶员在长时间驾驶过程中,因驾驶疲劳或分心造成注意力不集中能及时作出警示。文章比对目前国内外危险驾驶的检测方法,介绍了危险驾驶状态检测预警系统的设计流程及功能模块,并对系统中判断危险驾驶行为涉及的方法及关键技术作出分析,通过深度学习中人脸检测等相关算法模型以及多技术配合研究,更快速、更准确地实现驾驶员危险驾驶状态的检测和预警,有效降低交通事故发生概率。
The dangerous driving detection system is mainly used for the driver to give timely warnings due to inattention caused by driving fatigue or distraction during long-term driving.This paper compares the current domestic and foreign detection methods for dangerous driving,introduces the design process and functional modules of the dangerous driving state detection and early warning system,and analyzes the methods and key technologies involved in judging dangerous driving behavior in the system.Face detection and other related algorithm models and multi-technology cooperation research can more quickly and accurately realize the detection and early warning of drivers’dangerous driving states,and effectively reduce the probability of traffic accidents.
作者
许旻
马晨东
罗紫琳
Xu Min;Ma Chendong;Luo Zilin(College of Computer Engineering,Suzhou Vocational University,Suzhou 215104,China)
出处
《无线互联科技》
2022年第12期50-52,共3页
Wireless Internet Technology
基金
江苏省高等学校大学生创新创业训练计划项目,项目编号:202111054033T
苏州市职业大学教改项目(研究性课程),项目编号:SZDYKC-210607
全国高等院校计算机基础教育教学研究项目,项目编号:2021-AFCEC-082
苏州市职业大学教改项目,项目编号:SZDJG-21024。
关键词
危险驾驶
人脸检测
特征检测
深度学习
dangerous driving
face detection
feature detection
deep learning
