Advertisement

The Effect of Traffic Signals on the Macroscopic Fundamental Diagram

  • Boudewijn Zwaal
  • Victor L. KnoopEmail author
  • Hans van Lint
Conference paper

Abstract

Since the recent empirical evidence of the existence of the macroscopic fundamental diagram (MFD), there are already numerous applications for it, ranging from traffic management to traffic flow modelling. However, little is known what effect internal network control has on the shape of the MFD. This research will investigate the shape of an MFD on a regular network with and without traffic lights. To this end, we consider a regular grid network of infinite length. This is represented in a microscopic traffic simulation model as a two-ring network. We compare the situation without traffic lights to the situation with traffic lights with fixed timing. The uncontrolled case shows a higher flow for lower densities, while the controlled case shows a higher flow for higher densities. Analysis of the underlying process shows that this is due to the fact that traffic lights keep the vehicles spread more homogeneously over a network. In contrast, uncontrolled intersections result in an unstable situation where one part of the network becomes fully congested and the other part almost empty. This shows that traffic lights are reducing the performance for the low-density situations, but improving the traffic performance in high-density situation. In particular, the stability of a homogeneous spatial traffic distribution can be improved, even with fixed traffic light settings.

References

  1. 1.
    Daganzo, C.F.: Urban gridlock: macroscopic modeling and mitigation approaches. Transp. Res. Part B 41(1), 49–62 (2007). https://doi.org/10.1016/j.trb.2006.03.001 MathSciNetCrossRefGoogle Scholar
  2. 2.
    Daganzo, C.F., Geroliminis, N.: An analytical approximation for the macroscopic fundamental diagram of urban traffic. Transp. Res. Part B 42(9), 771–781 (2008). https://doi.org/10.1016/j.trb.2008.06.008 CrossRefGoogle Scholar
  3. 3.
    Daganzo, C.F., Gayah, V.V., Gonzales, E.J.: Macroscopic relations of urban traffic variables: bifurcations, multivaluedness and instability. Transp. Res. Part B Methodol. 45(1), 278–288 (2011). http://dx.doi.org/10.1016/j.trb.2010.06.006 CrossRefGoogle Scholar
  4. 4.
    De Jong, D., Knoop, V.L., Hoogendoorn, S.P.: The effect of signal settings on the macroscopic fundamental diagram and its applicability in traffic signal driven perimeter control strategies. In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (ITSC), 1010–1015 (2013).  https://doi.org/10.1109/ITSC.2013.6728364
  5. 5.
    Edie, L.: Discussion of traffic stream measurements and definitions. In: Organisation for Economic Co-operation and Development Proceedings, p. 139 (1965)Google Scholar
  6. 6.
    Gayah, V., Daganzo, C.: Effects of turning maneuvers and route choice on a simple network. Transp. Res. Rec. J. Transp. Res. Board 2249(1), 15–19 (2011). http://dx.doi.org/10.3141/2249-03 CrossRefGoogle Scholar
  7. 7.
    Gayah, V.V., Daganzo, C.F.: Clockwise hysteresis loops in the Macroscopic Fundamental Diagram: an effect of network instability. Transp. Res. Part B 45, 643–655 (2011). https://doi.org/10.1016/j.trb.2010.11.006 CrossRefGoogle Scholar
  8. 8.
    Gayah, V.V., Gao, X., Nagle, A.S.: On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram. Transp. Res. Part B 70, 255–268 (2014). https://doi.org/10.1016/j.trb.2014.09.010 CrossRefGoogle Scholar
  9. 9.
    Geroliminis, N., Daganzo, C.F.: Existence of urban-scale macroscopic fundamental diagrams: some experimental findings. Transp. Res. Part B 42(9), 759–770 (2008). https://doi.org/10.1016/j.trb.2008.02.002 CrossRefGoogle Scholar
  10. 10.
    Geroliminis, N., Sun, J.: Properties of a well-defined macroscopic fundamental diagram for urban traffic. Transp. Res. Part B 45, 605–617 (2011). https://doi.org/10.1016/j.trb.2010.11.004 CrossRefGoogle Scholar
  11. 11.
    Godfrey, J.: The mechanism of a road network. Traffic Eng. Control 11, 323–327 (1969)Google Scholar
  12. 12.
    Knoop, V.L., van Lint, H., Hoogendoorn, S.P.: Traffic dynamics: its impact on the Macroscopic Fundamental Diagram. Physica A Stat. Mech. Appl. 438, 236–250 (2015). http://dx.doi.org/10.1016/j.physa.2015.06.016. http://www.sciencedirect.com/science/article/pii/S0378437115005695 CrossRefGoogle Scholar
  13. 13.
    Malinauskas, R.: The Intelligent Driver Model: Analysis and Application to Adaptive Cruise Control (2014). http://tigerprints.clemson.edu/all_theses

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Boudewijn Zwaal
    • 1
  • Victor L. Knoop
    • 1
    Email author
  • Hans van Lint
    • 1
  1. 1.Delft University of TechnologyDelftThe Netherlands

Personalised recommendations