Yunran Di;Weihua Zhang;Heng Ding;Haotian Shi;Junwei You;Hangyu Li;Bin Ran
{"title":"A Cooperation Control for Multiple Urban Regions Traffic Flow Coupled With an Expressway Network","authors":"Yunran Di;Weihua Zhang;Heng Ding;Haotian Shi;Junwei You;Hangyu Li;Bin Ran","doi":"10.1109/TNSE.2025.3580759","DOIUrl":null,"url":null,"abstract":"As cities expand and long-distance travel demand increases, expressways are usually constructed to enhance regional connectivity. In the mixed road networks of urban roads and expressways, coordinating the distinct traffic dynamics of the two networks is a challenge. To address this challenge, we propose a cooperative flow control method for large-scale mixed networks. First, we develop an integrated traffic model that models urban regions using the macroscopic fundamental diagram (MFD) and expressways using the multi-class cell transmission model (CTM), achieving route tracking of vehicles throughout the entire mixed network. Next, a route choice model is developed to allocate new traffic demands within the mixed network. To coordinate traffic flow, a perimeter control (PC) is conducted to manage transfer flows between region boundaries, ramp metering (RM) to regulate flows entering expressways from urban regions, and variable speed limit (VSL) to control mainline speeds on expressways. We establish this cooperative flow control method within a model predictive control (MPC) framework. Case studies show that, based on the implementation of PC, the combined application of RM and VSL to the expressway system is more effective in reducing congestion and improving traffic efficiency in the mixed network than using RM and VSL independently.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 6","pages":"5058-5072"},"PeriodicalIF":7.9000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11045413/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
As cities expand and long-distance travel demand increases, expressways are usually constructed to enhance regional connectivity. In the mixed road networks of urban roads and expressways, coordinating the distinct traffic dynamics of the two networks is a challenge. To address this challenge, we propose a cooperative flow control method for large-scale mixed networks. First, we develop an integrated traffic model that models urban regions using the macroscopic fundamental diagram (MFD) and expressways using the multi-class cell transmission model (CTM), achieving route tracking of vehicles throughout the entire mixed network. Next, a route choice model is developed to allocate new traffic demands within the mixed network. To coordinate traffic flow, a perimeter control (PC) is conducted to manage transfer flows between region boundaries, ramp metering (RM) to regulate flows entering expressways from urban regions, and variable speed limit (VSL) to control mainline speeds on expressways. We establish this cooperative flow control method within a model predictive control (MPC) framework. Case studies show that, based on the implementation of PC, the combined application of RM and VSL to the expressway system is more effective in reducing congestion and improving traffic efficiency in the mixed network than using RM and VSL independently.
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.