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ORIGINAL RESEARCH article

Front. Phys.
Sec. Social Physics
Volume 12 - 2024 | doi: 10.3389/fphy.2024.1490499
This article is part of the Research Topic Network Learning and Propagation Dynamics Analysis View all 9 articles

Communication dynamics of congestion warning information considering the attitudes of travelers

Provisionally accepted
Huining Yan Huining Yan 1Hua Li Hua Li 2*Qiubai Sun Qiubai Sun 3Yuxi Jiang Yuxi Jiang 4
  • 1 School of Electronic and Information Engineering, University of Science and Technology LiaoNing, Anshan, China
  • 2 School of Business Administration, University of Science and Technology Liaoning, Anshan, China
  • 3 Asset Company, University of Science and Technology Liaoning, Anshan, China
  • 4 School of Economics and Management, Dalian Jiaotong University, Dalian, China

The final, formatted version of the article will be published soon.

    Traffic congestion is a serious problem faced by many cities worldwide today. Congestion warning information is one of the important influencing factors of urban road congestion; To this end, based on the dynamics of infectious diseases, a congestion warning information dissemination model considering the attitudes of travelers and the network structure was constructed. The existence and stability of the equilibrium points of non congestion warning information and congestion warning information in the model were analyzed, and the optimal control strategy of the model was proposed. Numerical simulation was conducted to verify the results of theoretical analysis, simulate and analyze the impact of changes in various parameters in the model on the dissemination of congestion warning information, and perform sensitivity analysis on several parameters. The results indicate that travelers are more inclined towards "fast" modes of transportation and have a stronger willingness to share congestion warning information. The dissemination range of warning information is wider, which can play a positive role in reducing traffic congestion pressure.

    Keywords: Congestion warning information, social networks, Communication dynamics, Traveler attitude, Optimum control

    Received: 03 Sep 2024; Accepted: 01 Oct 2024.

    Copyright: © 2024 Yan, Li, Sun and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Hua Li, School of Business Administration, University of Science and Technology Liaoning, Anshan, China

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