边缘计算在隧道车道控制中的应用与优化  

Application and Optimization of Edge Computing in Tunnel Lane Control

作　　者：王鹏[1] 钱治国[1] WANG Peng;QIAN Zhiguo(Gansu Vocational College of Communications,Lanzhou Gansu 730207,China)

机构地区：[1]甘肃交通职业技术学院,甘肃兰州730207

出　　处：《信息与电脑》2024年第5期25-27,共3页Information & Computer

基　　金：2022年度甘肃省高等学校创新基金项目(项目编号:2022A-232)。

摘　　要：主干公路中的隧道车道设计容量通常有限,当车流量超过道路的承载能力时容易导致拥堵。文章针对隧道中潮汐车道管理存在的问题,提出一种基于边缘计算的车道控制系统。首先,系统构建复杂的边缘节点,包括感知模块、通信模块、决策与控制模块等,实现拥堵时段的潮汐车道控制。其次,系统中的边缘节点以网络摄像头、工业计算机和车道控制器为基础,构建一个紧密合作的系统,充分发挥边缘计算的优势。最后,针对交通流量的变化,文章引入自适应车道控制策略,通过比例-积分-微分(Proportional-Integral-Derivative,PID)控制器动态调整相位时长,以提高车流通行效率。The design capacity of tunnel lanes in trunk roads is usually limited,which can easily lead to congestion when the traffic volume exceeds the carrying capacity of the road.This paper proposes a lane control system based on edge computing to address the problem of tidal lane management in tunnels.First,the system builds complex edge nodes,including sensing modules,communication modules,decision-making and control modules,etc.,to achieve tidal lane control during congestion periods.Secondly,the edge nodes in the system are based on network cameras,industrial computers and lane controllers to build a closely cooperating system,giving full play to the advantages of edge computing.Finally,in response to changes in traffic flow,this paper introduces an adaptive lane control strategy,which dynamically adjusts the phase duration through a Proportional-Integral-Derivative(PID)controller to optimize traffic flow efficiency.

关 键 词：边缘计算 车道控制 比例-积分-微分(PID)控制 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]