SDN-enabled Quantized LQR for Smart Traffic Light Controller to Optimize Congestion

IF 3.9 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

ACM Transactions on Internet Technology Pub Date : 2024-01-16 DOI:10.1145/3641104

Anuj Sachan, Neetesh Kumar

{"title":"SDN-enabled Quantized LQR for Smart Traffic Light Controller to Optimize Congestion","authors":"Anuj Sachan, Neetesh Kumar","doi":"10.1145/3641104","DOIUrl":null,"url":null,"abstract":"<p>Existing intersection management systems, in urban cities, lack in meeting the current requirements of self-configuration, lightweight computing, and software-defined control, which are necessarily required for congested road-lane networks. To satisfy these requirements, this work proposes effective, scalable, multi-input and multi-output, and congestion prevention enabled intersection management system utilizing a software-defined control interface that not only regularly monitors the traffic to prevent congestion for minimizing queue length and waiting time, it also offers a computationally efficient solution in real-time. For effective intersection management, a modified linear-quadratic regulator, i.e., Quantized Linear Quadratic Regulator (QLQR), is designed along with Software-Defined Networking (SDN) enabled control interface to maximize throughput and vehicles speed and minimize queue length and waiting time at the intersection. Experimental results prove that the proposed SDN-QLQR improves the comparative performance in the interval of 24.94% – 49.07%, 35.78% – 68.86%, 36.67% – 59.08%, and 29.94% – 57.87% for various performance metrics, i.e., average queue length, average waiting time, throughput, and average speed respectively.</p>","PeriodicalId":50911,"journal":{"name":"ACM Transactions on Internet Technology","volume":"10 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Internet Technology","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3641104","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Existing intersection management systems, in urban cities, lack in meeting the current requirements of self-configuration, lightweight computing, and software-defined control, which are necessarily required for congested road-lane networks. To satisfy these requirements, this work proposes effective, scalable, multi-input and multi-output, and congestion prevention enabled intersection management system utilizing a software-defined control interface that not only regularly monitors the traffic to prevent congestion for minimizing queue length and waiting time, it also offers a computationally efficient solution in real-time. For effective intersection management, a modified linear-quadratic regulator, i.e., Quantized Linear Quadratic Regulator (QLQR), is designed along with Software-Defined Networking (SDN) enabled control interface to maximize throughput and vehicles speed and minimize queue length and waiting time at the intersection. Experimental results prove that the proposed SDN-QLQR improves the comparative performance in the interval of 24.94% – 49.07%, 35.78% – 68.86%, 36.67% – 59.08%, and 29.94% – 57.87% for various performance metrics, i.e., average queue length, average waiting time, throughput, and average speed respectively.

查看原文本刊更多论文

用于智能交通灯控制器的 SDN 量化 LQR 可优化拥堵状况

城市中现有的交叉口管理系统无法满足当前对自配置、轻量级计算和软件定义控制的要求，而这正是拥堵的道路车道网络所必须的。为满足这些要求，本研究提出了有效、可扩展、多输入和多输出、可预防拥堵的交叉口管理系统，该系统利用软件定义的控制界面，不仅能定期监控交通，预防拥堵，从而最大限度地减少排队长度和等待时间，还能实时提供计算效率高的解决方案。为实现有效的交叉路口管理，设计了一种改进的线性二次调节器，即量化线性二次调节器（QLQR），并配备了软件定义网络（SDN）控制界面，以最大限度地提高吞吐量和车速，并最大限度地减少交叉路口的队列长度和等待时间。实验结果证明，就平均队列长度、平均等待时间、吞吐量和平均速度等各种性能指标而言，所提出的 SDN-QLQR 可分别在 24.94% - 49.07%、35.78% - 68.86%、36.67% - 59.08% 和 29.94% - 57.87% 的区间内提高比较性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

ACM Transactions on Internet Technology 工程技术-计算机：软件工程

CiteScore

10.30

自引率

1.90%

发文量

137

审稿时长

>12 weeks

期刊介绍： ACM Transactions on Internet Technology (TOIT) brings together many computing disciplines including computer software engineering, computer programming languages, middleware, database management, security, knowledge discovery and data mining, networking and distributed systems, communications, performance and scalability etc. TOIT will cover the results and roles of the individual disciplines and the relationshipsamong them.