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The effect of variability of urban systems characteristics in the network capacity

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  • Geroliminis, Nikolas
  • Boyacı, Burak

Abstract

Recent experimental analysis has shown that some types of urban networks exhibit a low scatter reproducible relationship between average network flow and density, known as the macroscopic fundamental diagram (MFD). It has also been shown that heterogeneity in the spatial distribution of density can significantly decrease the network flow for the same value of density. Analytical theories have been developed to explore the connection between network structure and an MFD for urban neighborhoods with cars controlled by traffic signals. However these theories have been applied only in cities with deterministic values of topological and control variables for the whole network and by ignoring the effect of turns. In our study we are aiming to generate an MFD for streets with variable link lengths and signal characteristics and understand the effect of variability for different cities and signal structures. Furthermore, this variability gives the opportunity to mimic the effect of turning movements. Route or network capacity can be significantly smaller than the capacity of a single link, because of the correlations developed through the different values of offsets. The above analysis would not be possible using standard traffic engineering techniques. This will be a key issue in planning the signal regimes such a way that maximizes the network capacity and/or the density range of the maximum capacity.

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  • Geroliminis, Nikolas & Boyacı, Burak, 2012. "The effect of variability of urban systems characteristics in the network capacity," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1607-1623.
    • Handle: RePEc:eee:transb:v:46:y:2012:i:10:p:1607-1623
    DOI: 10.1016/j.trb.2012.08.001
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    References listed on IDEAS

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    12. Geroliminis, Nikolas & Sun, Jie, 2011. "Hysteresis phenomena of a Macroscopic Fundamental Diagram in freeway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 966-979, November.
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    Cited by:

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    3. Ambühl, Lukas & Loder, Allister & Bliemer, Michiel C.J. & Menendez, Monica & Axhausen, Kay W., 2020. "A functional form with a physical meaning for the macroscopic fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 119-132.
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    6. Xianglun Mo & Xiaohong Jin & Jinpeng Tian & Zhushuai Shao & Gangqing Han, 2022. "Research on the Division Method of Signal Control Sub-Region Based on Macroscopic Fundamental Diagram," Sustainability, MDPI, vol. 14(13), pages 1-19, July.
    7. Zheng, Nan & Geroliminis, Nikolas, 2013. "On the distribution of urban road space for multimodal congested networks," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 326-341.
    8. Ma, Wenfei & Huang, Yunping & Jin, Xiao & Zhong, Renxin, 2024. "Functional form selection and calibration of macroscopic fundamental diagrams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    9. Yao, Wenbin & Chen, Nuo & Su, Hongyang & Hu, Youwei & Jin, Sheng & Rong, Donglei, 2023. "A novel self-adaption macroscopic fundamental diagram considering network heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    10. Du, Jie & Wong, S.C. & Shu, Chi-Wang & Zhang, Mengping, 2015. "Reformulating the Hoogendoorn–Bovy predictive dynamic user-optimal model in continuum space with anisotropic condition," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 189-217.
    11. Zhang, Lele & Finn, Caley & Garoni, Timothy M. & de Gier, Jan, 2018. "Behaviour of traffic on a link with traffic light boundaries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 116-138.
    12. Liu, Wei & Geroliminis, Nikolas, 2016. "Modeling the morning commute for urban networks with cruising-for-parking: An MFD approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 470-494.
    13. Du, Jie & Wong, S.C. & Shu, Chi-Wang & Xiong, Tao & Zhang, Mengping & Choi, Keechoo, 2013. "Revisiting Jiang’s dynamic continuum model for urban cities," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 96-119.
    14. Leclercq, Ludovic & Geroliminis, Nikolas, 2013. "Estimating MFDs in simple networks with route choice," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 468-484.
    15. 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.
    16. Zhaoqi Zang & Xiangdong Xu & Anthony Chen & Chao Yang, 2022. "Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation," Transportation, Springer, vol. 49(4), pages 1211-1243, August.
    17. Alonso, Borja & Ibeas, Ángel & Musolino, Giuseppe & Rindone, Corrado & Vitetta, Antonino, 2019. "Effects of traffic control regulation on Network Macroscopic Fundamental Diagram: A statistical analysis of real data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 136-151.
    18. Haddad, Jack & Shraiber, Arie, 2014. "Robust perimeter control design for an urban region," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 315-332.
    19. Ramezani, Mohsen & Haddad, Jack & Geroliminis, Nikolas, 2015. "Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 1-19.
    20. Hans, Etienne & Chiabaut, Nicolas & Leclercq, Ludovic, 2015. "Applying variational theory to travel time estimation on urban arterials," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 169-181.
    21. Zheng, Nan & Geroliminis, Nikolas, 2016. "Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 36-58.
    22. Ding, Heng & Qian, Yu & Zheng, Xiaoyan & Bai, Haijian & Wang, Shiguang & Zhou, Jingwen, 2022. "Dynamic parking charge–perimeter control coupled method for a congested road network based on the aggregation degree characteristics of parking generation distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).

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