智能车辆管理中的驾驶行为检测
Driving behavior detection in intelligent vehicle management
徐翔 1陈震2
作者信息
- 1. 中国三峡新能源(集团)股份有限公司,北京 101100
- 2. 中国三峡新能源(集团)股份有限公司建设管理分公司
- 折叠
摘要
在智能交通系统的背景下,车辆管理模式的创新对于提高交通安全和管理效率至关重要.针对驾驶中的不良行为,提出一种基于深度学习的检测方法.通过引入并改进YOLOV5算法,能够实时检测驾驶员的不良行为,从而降低交通事故的风险.实验结果显示,所提算法有效提高了不良驾驶行为的检测精度.这种车辆管理模式创新可以为未来智能交通系统的发展提供参考与借鉴.
Abstract
In the context of intelligent transportation system,the innovation of vehicle management mode is very important to improve traffic safety and management efficiency.A deep learning-based detection method is proposed for bad behaviors in driving.By introducing and improving the YOLOV5 algorithm,the bad behaviors of drivers can be detected in real time,thus reducing the risk of traffic accidents.The experimental results show that the proposed algorithm can effectively improve the detection accuracy of bad driving behavior.This vehicle management model innovation can provide reference for the future development of intelligent transportation system.
关键词
深度学习/驾驶行为/车辆管理模式/注意力机制Key words
deep learning/driving behavior/vehicle management mode/attention mechanism引用本文复制引用
出版年
2023
NETL
NSTL
维普
万方数据