Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145912
Title: Research on a model of node and path selection for traffic network congestion evacuation based on complex network theory
Authors: Zhang, Guilan
Jia, Hongfei
Yang, Lili
Li, Yongxing
Yang, Jinling
Keywords: Engineering::Civil engineering
Issue Date: 2019
Source: Zhang, G., Jia, H., Yang, L., Li, Y., & Yang, J. (2020). Research on a model of node and path selection for traffic network congestion evacuation based on complex network theory. IEEE Access, 8, 7506-7517. doi:10.1109/ACCESS.2019.2959654
Journal: IEEE Access
Abstract: Based on relevant complex network theory, this paper analyzes the characterization parameters of traffic network complexity, such as the causes of traffic congestion and evacuation models. From the perspective of the traffic capacity of traffic network nodes, combined with the transit time of each road, model is proposed for selecting the weights of congestion evacuation nodes. According to the evacuation target, combined with characteristic parameters, such as node degree, node strength, clustering coefficient and closeness, the grey system evaluation method and the analytic hierarchy process (AHP)are combined. Based on the grey relational analysis model, a model is established for determining the priority connectivity evaluation value of each node. The complex characteristics of the actual traffic network in the Chaoyang District of Changchun City are analyzed, then the selection weights of each node of the traffic network are obtained. Having defined the distance between complex network nodes, a congestion evacuation path selection model is proposed, and an evacuation path scheme is given for specified start and end points.
URI: https://hdl.handle.net/10356/145912
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2959654
Schools: School of Civil and Environmental Engineering 
Rights: © 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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