现代信息科技2024，Vol.8Issue(17)：179-184,6.DOI:10.19850/j.cnki.2096-4706.2024.17.035
基于深度学习的智能交通灯设计
Design of Intelligent Transportation Light Based on Deep Learning
摘要
Abstract
In view of the inflexibility of the passage time in traditional transportation light,an intelligent transportation light based on Deep Learning is designed through research on the traffic flow information collected under the transportation light.Firstly,the lane lines are extracted using FCN,and a clustering algorithm is used to fit the lane line function.Secondly,the SSD network model is extracted,with the VGG network as the backbone feature of model,to detect the positional information of vehicles,and the positional information of vehicles is combined with the positional information of lane lines to count the traffic flow information of each lane under the transportation light.The experimental results show that the intelligent transportation light system based on Deep Learning has an accuracy of 90.69%in the actual application process,which is basically applied in the real environment.关键词
车辆检测/SSD/FCN/智能交通Key words
vehicle detection/SSD/FCN/intelligent transportation分类
信息技术与安全科学引用本文复制引用
孔令龙,任仕艳..基于深度学习的智能交通灯设计[J].现代信息科技,2024,8(17):179-184,6.
