基于神经网络的智能交通系统交通信号灯设计  

Traffic light design of intelligent transportation system based on neural network

作　　者：丁璇[1] DING Xuan(Shanxi Police Vocational College,Xi’an 710021,China)

机构地区：[1]陕西警官职业学院,陕西西安710021

出　　处：《中国高新科技》2023年第17期22-24,共3页

摘　　要：随着城市生活节奏的加快,通过设计智能的交通控制系统提高交通效率是一个重要途径。文章以神经网络在智能交通控制系统中涉及的交通模式分析、交通流量预测、交通控制方式选择等方面的应用为基础,对车流量及车道通行能力、神经网络的模型设计与车流量检测、神经网络模型训练、GUI设计与系统测试进行科学设计与详细分析,以此为实现智能交通灯控制系统的设计提供有益参考,进而实现对信号灯的智能控制,有效缩短车辆在路口的等待时间,缓解交通拥堵。As urban life quickens its pace,developing intelligent traffic control systems to bolster transportation efficiency has become paramount.This study delves into the deployment of neural networks within the realm of intelligent traffic control systems,concentrating on pivotal components such as analysis of traffic patterns,prediction of traffic flow,and the discernment of the most effective traffic control strategies.We undertake a rigorous design and thorough analysis of traffic volume and lane capacity,as well as the modeling of neural networks for traffic flow detection.Furthermore,the training of neural network models,the design of the Graphical User Interface(GUI),and system testing are systematically addressed.This work offers a valuable reference for those aiming to design an intelligent traffic light control system,thereby promoting the smart regulation of traffic signals.This enhancement effectively curtails the waiting duration of vehicles at intersections and mitigates traffic congestion.

关 键 词：BP神经网络 智能交通 信号灯控制 车流检测 图形用户界面 

分 类 号：TN929[电子电信—通信与信息系统]