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An empirical analysis on the arterial fundamental diagram


  • Wu, Xinkai
  • Liu, Henry X.
  • Geroliminis, Nikolas


For uninterrupted traffic flow, it is well-known that the fundamental diagram (FD) describes the relationship between traffic flow and density under steady state. For interrupted traffic flow on a signalized road, it has been recognized that the arterial fundamental diagram (AFD) is significantly affected by signal operations. But little research up to date has discussed in detail how signal operations impact the AFD. In this paper, based upon empirical observations from high-resolution event-based traffic signal data collected from a major arterial in the Twin Cities area, we study the impacts of g/C ratio, signal coordination, and turning movements on the cycle-based AFD, which describes the relationship between traffic flow and occupancy in a signal cycle. By microscopically investigating individual vehicle trajectories from event-based data, we demonstrate that not only g/C ratio constrains the capacity of a signalized approach, poor signal coordination and turning movements from upstream intersections also have significant impact on the capacity. We show that an arterial link may not be congested even with high occupancy values. Such high values could result from queue build-up during red light that occupies the detector, i.e. the Queue-Over-Detector (QOD) phenomenon discussed in this paper. More importantly, by removing the impact of QOD, a stable form of AFD is revealed, and one can use that to identify three different regimes including under-saturation, saturation, and over-saturation with queue spillovers. We believe the stable form of AFD is of great importance for traffic signal control because of its ability to identify traffic states on a signal link.

Suggested Citation

  • Wu, Xinkai & Liu, Henry X. & Geroliminis, Nikolas, 2011. "An empirical analysis on the arterial fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 255-266, January.
  • Handle: RePEc:eee:transb:v:45:y:2011:i:1:p:255-266

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    References listed on IDEAS

    1. 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.
    2. Kerner, Boris S., 2004. "Three-phase traffic theory and highway capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 379-440.
    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.
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    Cited by:

    1. 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.
    2. 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.
    3. repec:eee:transb:v:104:y:2017:i:c:p:256-271 is not listed on IDEAS
    4. Qu, Xiaobo & Wang, Shuaian & Zhang, Jin, 2015. "On the fundamental diagram for freeway traffic: A novel calibration approach for single-regime models," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 91-102.
    5. 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.
    6. Tian, Junfang & Treiber, Martin & Ma, Shoufeng & Jia, Bin & Zhang, Wenyi, 2015. "Microscopic driving theory with oscillatory congested states: Model and empirical verification," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 138-157.
    7. Hao, Peng & Ban, Xuegang, 2015. "Long queue estimation for signalized intersections using mobile data," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 54-73.


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