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Effects of road network structure on the performance of urban traffic systems

Author

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  • Wu, Chao-Yun
  • Hu, Mao-Bin
  • Jiang, Rui
  • Hao, Qing-Yi

Abstract

Urban traffic system is important for the convenience and efficiency of people’s daily life. The understanding of inter-relations between urban street network and traffic flow can help the planning process of urban systems. Based on cellular automata modeling, this paper studies the influence of aspect ratio of a rectangular urban network on the dynamics of traffic system. The performance of road network is examined with the Macroscopic Fundamental Diagram (MFD). The maximal arrival rate and the critical density of congestion of MFD are investigated as two main indicators for system performance. Under the closed boundary condition, the square network shows the maximum arrival rate, but with a relatively lower critical density of congestion. With the increase of aspect ratio, the arrival rate decreases, while the critical congestion density increases. The phenomena can be explained by the vehicle distribution in the network, the left-turning and U-turning demand, and the average travel distance.

Suggested Citation

  • Wu, Chao-Yun & Hu, Mao-Bin & Jiang, Rui & Hao, Qing-Yi, 2021. "Effects of road network structure on the performance of urban traffic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
  • Handle: RePEc:eee:phsmap:v:563:y:2021:i:c:s0378437120307160
    DOI: 10.1016/j.physa.2020.125361
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    1. Meisam Akbarzadeh & Soroush Memarmontazerin & Sybil Derrible & Sayed Farzin Salehi Reihani, 2019. "Correction to: The role of travel demand and network centrality on the connectivity and resilience of an urban street system," Transportation, Springer, vol. 46(5), pages 1969-1969, October.
    2. Laval, Jorge A. & Castrillón, Felipe, 2015. "Stochastic approximations for the macroscopic fundamental diagram of urban networks," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 904-916.
    3. D. Helbing, 2009. "Derivation of a fundamental diagram for urban traffic flow," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 70(2), pages 229-241, July.
    4. Ding, Rui & Ujang, Norsidah & Hamid, Hussain bin & Manan, Mohd Shahrudin Abd & He, Yuou & Li, Rong & Wu, Jianjun, 2018. "Detecting the urban traffic network structure dynamics through the growth and analysis of multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 800-817.
    5. Zhang, Lele & Garoni, Timothy M & de Gier, Jan, 2013. "A comparative study of Macroscopic Fundamental Diagrams of arterial road networks governed by adaptive traffic signal systems," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 1-23.
    6. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    7. Daganzo, Carlos F. & Gayah, Vikash V. & Gonzales, Eric J., 2011. "Macroscopic relations of urban traffic variables: Bifurcations, multivaluedness and instability," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 278-288, January.
    8. M.-B. Hu & R. Jiang & Y.-H. Wu & W.-X. Wang & Q.-S. Wu, 2008. "Urban traffic from the perspective of dual graph," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 63(1), pages 127-133, May.
    9. Chowdhury, Debashish & Wolf, Dietrich E. & Schreckenberg, Michael, 1997. "Particle hopping models for two-lane traffic with two kinds of vehicles: Effects of lane-changing rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 235(3), pages 417-439.
    10. Daganzo, Carlos F. & Knoop, Victor L., 2016. "Traffic flow on pedestrianized streets," Transportation Research Part B: Methodological, Elsevier, vol. 86(C), pages 211-222.
    11. Meisam Akbarzadeh & Soroush Memarmontazerin & Sybil Derrible & Sayed Farzin Salehi Reihani, 2019. "The role of travel demand and network centrality on the connectivity and resilience of an urban street system," Transportation, Springer, vol. 46(4), pages 1127-1141, August.
    12. Daganzo, Carlos F. & Geroliminis, Nikolas, 2008. "An analytical approximation for the macroscopic fundamental diagram of urban traffic," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 771-781, November.
    13. Daganzo, Carlos F & Geroliminis, Nikolas, 2008. "An analytical approximation for the macropscopic fundamental diagram of urban traffic," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4cb8h3jm, Institute of Transportation Studies, UC Berkeley.
    14. Lämmer, Stefan & Gehlsen, Björn & Helbing, Dirk, 2006. "Scaling laws in the spatial structure of urban road networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 89-95.
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