现代电子技术2024，Vol.47Issue(14)：157-161,5.DOI:10.16652/j.issn.1004-373x.2024.14.024
基于深度学习的汽车防追尾预警系统设计
Design of automobile rear end collision prevention warning system based on deep learning
叶浩 1徐今强 1皮雨蒙 2左康渝2
作者信息
- 1. 广东海洋大学 电子与信息工程学院,广东 湛江 524088
- 2. 华南农业大学 经济管理学院,广东 广州 510642
- 折叠
摘要
Abstract
In allusion to the current mainstream rear end collision prevention systems,there is a common problem of single identification factors and insufficient prevention effect on the driver themselves.A deep learning based automotive rear end collision prevention warning system is designed,which can integrate YOLOv5 pruning technology,attention mechanism,PID optimizer and other methods into the training of network models to optimize model accuracy and reduce model volume.The rear end risk of vehicles is calculated mainly based on distance judgment,and supplemented by speed,acceleration,and accident hazard judgment.After each warning,the data is uploaded to the Internet of Things platform by means of the MQTT protocol,and safety analysis is conducted on the driver when the system ends running.The system is ultimately deployed in the TensorRT environment for the further optimization.The experimental results show that the designed car rear end collision prevention warning system has fast response speed,strong adaptability,and accurate risk assessment.关键词
汽车防追尾系统/深度学习/YOLOv5/物联网/追尾判断/风险预警Key words
car rear end collision prevention system/deep learning/YOLOv5/Internet of Things/tail end judgment/risk warning分类
信息技术与安全科学引用本文复制引用
叶浩,徐今强,皮雨蒙,左康渝..基于深度学习的汽车防追尾预警系统设计[J].现代电子技术,2024,47(14):157-161,5.
