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Simple abstract models to study stability of urban networks with decentralized signal control

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  • Gupta, Namrata
  • Patil, Gopal R.
  • Vu, Hai L.

Abstract

Traffic Signal Controllers (TSCs) used to manage intersections can influence the residual queues at intersections. These residual queues can lead to an irreversible state of network gridlock. This paper discovers the advantages of locally adaptive TSCs utilizing traffic information on both upstream and downstream approaches of an intersection (e.g., back-pressure or BP control) over employing only upstream approaches information (e.g., proportional control) in avoiding gridlock. Although BP algorithms are mathematically proven to be throughput optimal as they bound network queues for all feasible demands, the proofs exist only for networks with infinite link capacities, fixed-route choices, or for TSCs with no minimum green-time requirement.

Suggested Citation

  • Gupta, Namrata & Patil, Gopal R. & Vu, Hai L., 2023. "Simple abstract models to study stability of urban networks with decentralized signal control," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 93-116.
    • Handle: RePEc:eee:transb:v:172:y:2023:i:c:p:93-116
    DOI: 10.1016/j.trb.2023.03.013
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    References listed on IDEAS

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    1. Geroliminis, Nikolas, 2015. "Cruising-for-parking in congested cities with an MFD representation," Economics of Transportation, Elsevier, vol. 4(3), pages 156-165.
    2. 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.
    3. Jin, Wen-Long & Gan, Qi-Jian & Gayah, Vikash V., 2013. "A kinematic wave approach to traffic statics and dynamics in a double-ring network," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 114-131.
    4. 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.
    5. Gu, Ziyuan & Safarighouzhdi, Farshid & Saberi, Meead & Rashidi, Taha H., 2021. "A macro-micro approach to modeling parking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 220-244.
    6. Haddad, Jack & Ramezani, Mohsen & Geroliminis, Nikolas, 2013. "Cooperative traffic control of a mixed network with two urban regions and a freeway," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 17-36.
    7. Zheng, Nan & Waraich, Rashid A. & Axhausen, Kay W. & Geroliminis, Nikolas, 2012. "A dynamic cordon pricing scheme combining the Macroscopic Fundamental Diagram and an agent-based traffic model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1291-1303.
    8. Mohajerpoor, Reza & Saberi, Meead & Ramezani, Mohsen, 2019. "Analytical derivation of the optimal traffic signal timing: Minimizing delay variability and spillback probability for undersaturated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 45-68.
    9. Zhang, Zhao & Parr, Scott A. & Jiang, Hai & Wolshon, Brian, 2015. "Optimization model for regional evacuation transportation system using macroscopic productivity function," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 616-630.
    10. Yildirimoglu, Mehmet & Geroliminis, Nikolas, 2014. "Approximating dynamic equilibrium conditions with macroscopic fundamental diagrams," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 186-200.
    11. Lele Zhang & Zhongqi Yuan & Li Yang & Zhiyuan Liu, 2020. "Recent developments in traffic flow modelling using macroscopic fundamental diagram," Transport Reviews, Taylor & Francis Journals, vol. 40(6), pages 689-710, November.
    12. Gayah, Vikash V. & Gao, Xueyu (Shirley) & Nagle, Andrew S., 2014. "On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 255-268.
    13. 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.
    14. 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).
    15. Li, Ye & Mohajerpoor, Reza & Ramezani, Mohsen, 2021. "Perimeter control with real-time location-varying cordon," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 101-120.
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