CPS-oriented Modeling and Control of Traffic Signals Using Adaptive Back Pressure

Wanli Chang, Debayan Roy, Shuai Zhao, A. Annaswamy, S. Chakraborty
{"title":"CPS-oriented Modeling and Control of Traffic Signals Using Adaptive Back Pressure","authors":"Wanli Chang, Debayan Roy, Shuai Zhao, A. Annaswamy, S. Chakraborty","doi":"10.23919/DATE48585.2020.9116403","DOIUrl":null,"url":null,"abstract":"Modeling and design of automotive systems from a cyber-physical system (CPS) perspective have lately attracted extensive attention. As the trend towards automated driving and connectivity accelerates, strong interactions between vehicles and the infrastructure are expected. This requires modeling and control of the traffic network in a similarly formal manner. Modeling of such networks involves a tradeoff between expressivity of the appropriate features and tractability of the control problem. Back-pressure control of traffic signals is gaining ground due to its decentralized implementation, low computational complexity, and no requirements on prior traffic information. It guarantees maximum stability under idealistic assumptions. However, when deployed in real traffic intersections, the existing back-pressure control algorithms may result in poor junction utilization due to (i) fixed-length control phases; (ii) stability as the only objective; and (iii) obliviousness to finite road capacities and empty roads. In this paper, we propose a CPS-oriented model of traffic intersections and control of traffic signals, aiming to address the utilization issue of the back-pressure algorithms. We consider a more realistic model with transition phases and dedicated turning lanes, the latter influencing computation of the pressure and subsequently the utilization. The main technical contribution is an adaptive controller that enables varying-length control phases and considers both stability and utilization, while taking both cases of full roads and empty roads into account. We implement a mechanism to prevent frequent changes of control phases and thus limit the number of transition phases, which have negative impact on the junction utilization. Microscopic simulation results with SUMO on a 3×3 traffic network under various traffic patterns show that the proposed algorithm is at least about 13% better in performance than the existing fixed-length backpressure control algorithms reported in previous works. This is a significant improvement in the context of traffic signal control.","PeriodicalId":289525,"journal":{"name":"2020 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/DATE48585.2020.9116403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Modeling and design of automotive systems from a cyber-physical system (CPS) perspective have lately attracted extensive attention. As the trend towards automated driving and connectivity accelerates, strong interactions between vehicles and the infrastructure are expected. This requires modeling and control of the traffic network in a similarly formal manner. Modeling of such networks involves a tradeoff between expressivity of the appropriate features and tractability of the control problem. Back-pressure control of traffic signals is gaining ground due to its decentralized implementation, low computational complexity, and no requirements on prior traffic information. It guarantees maximum stability under idealistic assumptions. However, when deployed in real traffic intersections, the existing back-pressure control algorithms may result in poor junction utilization due to (i) fixed-length control phases; (ii) stability as the only objective; and (iii) obliviousness to finite road capacities and empty roads. In this paper, we propose a CPS-oriented model of traffic intersections and control of traffic signals, aiming to address the utilization issue of the back-pressure algorithms. We consider a more realistic model with transition phases and dedicated turning lanes, the latter influencing computation of the pressure and subsequently the utilization. The main technical contribution is an adaptive controller that enables varying-length control phases and considers both stability and utilization, while taking both cases of full roads and empty roads into account. We implement a mechanism to prevent frequent changes of control phases and thus limit the number of transition phases, which have negative impact on the junction utilization. Microscopic simulation results with SUMO on a 3×3 traffic network under various traffic patterns show that the proposed algorithm is at least about 13% better in performance than the existing fixed-length backpressure control algorithms reported in previous works. This is a significant improvement in the context of traffic signal control.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于cps的自适应背压交通信号建模与控制
基于信息物理系统(CPS)的汽车系统建模与设计近年来受到了广泛关注。随着自动驾驶和互联趋势的加速,车辆与基础设施之间的强烈互动有望实现。这需要以类似的正式方式对交通网络进行建模和控制。这种网络的建模涉及到适当特征的表达性和控制问题的可跟踪性之间的权衡。交通信号背压控制因其分散实现、计算复杂度低、不需要预先获取交通信息等优点而得到广泛应用。它保证了理想主义假设下的最大稳定性。然而,当部署在实际交通路口时,现有的背压控制算法可能会由于(1)固定长度的控制阶段而导致交叉口利用率低下;稳定作为唯一目标;(三)对有限的道路容量和空旷道路的遗忘。在本文中,我们提出了一个面向cps的交通路口和交通信号控制模型,旨在解决背压算法的利用问题。我们考虑了一个具有过渡阶段和专用转弯车道的更现实的模型,后者影响压力的计算和随后的利用。主要的技术贡献是一个自适应控制器,它可以实现变长控制阶段,同时考虑稳定性和利用率,同时考虑满路和空路两种情况。我们实现了一种机制来防止控制阶段的频繁变化,从而限制过渡阶段的数量,这对结的利用率有负面影响。在3×3交通网络上的SUMO微观仿真结果表明,与已有的定长背压控制算法相比,本文算法的性能至少提高了13%左右。这在交通信号控制方面是一个重大的改进。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
In-Memory Resistive RAM Implementation of Binarized Neural Networks for Medical Applications Towards Formal Verification of Optimized and Industrial Multipliers A 100KHz-1GHz Termination-dependent Human Body Communication Channel Measurement using Miniaturized Wearable Devices Computational SRAM Design Automation using Pushed-Rule Bitcells for Energy-Efficient Vector Processing PIM-Aligner: A Processing-in-MRAM Platform for Biological Sequence Alignment
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1