{"title":"Research on route hierarchical control strategy from the perspective of macroscopic traffic network","authors":"Leilei Kang , Weike Lu , Lan Liu","doi":"10.1080/15472450.2022.2084337","DOIUrl":null,"url":null,"abstract":"<div><div>In order to alleviate traffic congestion, transfer the regional orientation of macroscopic traffic flow to microscopic routes, and form a unified and coordinated framework of macro path decision and micro path decision, a vehicle route hierarchical control strategy is proposed from the perspective of network macro aggregated information. Firstly, according to the homogeneity of vehicle density distribution, a network is divided into several sub-regions, and then the macro-aggregate dynamic mapping relationship of each sub-area is analyzed. Secondly, a traffic equilibrium distribution model is established under heterogeneous macro path conditions to minimize the travel time of traffic flow. To bring macro traffic flow solved by the above model to the projected into the actual network level, the logit route model is used to guide macro traffic flow to the micro-scale road network with the help of a simplified network. Finally, the SUMO simulation platform is employed to achieve the solution and verification of the hierarchical vehicle path control method. The experimental results prove that the strategy can effectively reduce the congestion of the urban road network during peak hours and improve the traffic capacity of the road network. It is also demonstrated that macroscopic aggregate information is one of the reliable information sources for vehicle path control and guidance in a road network.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"27 6","pages":"Pages 818-833"},"PeriodicalIF":2.8000,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Transportation Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1547245022004376","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
In order to alleviate traffic congestion, transfer the regional orientation of macroscopic traffic flow to microscopic routes, and form a unified and coordinated framework of macro path decision and micro path decision, a vehicle route hierarchical control strategy is proposed from the perspective of network macro aggregated information. Firstly, according to the homogeneity of vehicle density distribution, a network is divided into several sub-regions, and then the macro-aggregate dynamic mapping relationship of each sub-area is analyzed. Secondly, a traffic equilibrium distribution model is established under heterogeneous macro path conditions to minimize the travel time of traffic flow. To bring macro traffic flow solved by the above model to the projected into the actual network level, the logit route model is used to guide macro traffic flow to the micro-scale road network with the help of a simplified network. Finally, the SUMO simulation platform is employed to achieve the solution and verification of the hierarchical vehicle path control method. The experimental results prove that the strategy can effectively reduce the congestion of the urban road network during peak hours and improve the traffic capacity of the road network. It is also demonstrated that macroscopic aggregate information is one of the reliable information sources for vehicle path control and guidance in a road network.
期刊介绍:
The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new.
The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption.
The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.