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A game theory model of urban public traffic networks

Author

Listed:
  • Su, B.B.
  • Chang, H.
  • Chen, Y.-Z.
  • He, D.R.

Abstract

We have studied urban public traffic networks from the viewpoint of complex networks and game theory. Firstly, we have empirically investigated an urban public traffic network in Beijing in 2003, and obtained its statistical properties. Then a simplified game theory model is proposed for simulating the evolution of the traffic network. The basic idea is that three network manipulators, passengers, an urban public traffic company, and a government traffic management agency, play games in a network evolution process. Each manipulator tries to build the traffic lines to magnify its “benefit”. Simulation results show a good qualitative agreement with the empirical results.

Suggested Citation

  • Su, B.B. & Chang, H. & Chen, Y.-Z. & He, D.R., 2007. "A game theory model of urban public traffic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 291-297.
    • Handle: RePEc:eee:phsmap:v:379:y:2007:i:1:p:291-297
    DOI: 10.1016/j.physa.2006.12.049
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    Citations

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    Cited by:

    1. Beata Grzyl & Magdalena Apollo & Adam Kristowski, 2019. "Application of Game Theory to Conflict Management in a Construction Contract," Sustainability, MDPI, vol. 11(7), pages 1-12, April.
    2. Yuan, PengCheng & Juan, ZhiCai, 2013. "The related congestion failure estimating methodology and model in transportation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4330-4344.
    3. Yuan, PengCheng & Lin, XuXun, 2017. "How long will the traffic flow time series keep efficacious to forecast the future?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 419-431.
    4. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
    5. Lin, XuXun & Yuan, PengCheng, 2018. "A dynamic parking charge optimal control model under perspective of commuters’ evolutionary game behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1096-1110.
    6. Chang, Hui & Xu, Xiu-Lian & Hu, Chin-Kun & Fu, Chunhua & Feng, Ai-xia & He, Da-Ren, 2014. "A manipulator game model of urban public traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 378-385.
    7. Sarita Gajbhiye Meshram & Maryam Adhami & Ozgur Kisi & Chandrashekhar Meshram & Pham Anh Duc & Khaled Mohamed Khedher, 2021. "Identification of Critical Watershed for Soil Conservation Using Game Theory-Based Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3105-3120, August.
    8. Yao, Wang & Jia, Ning & Zhong, Shiquan & Li, Liying, 2018. "Best response game of traffic on road network of non-signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 386-401.

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