A Framework for the Evaluation of Methods for Road Traffic Assignment

  • Syed Galib
  • Irene Moser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8272)


Research in traffic assignment relies largely on experimentation. The outcomes of experiments using different traffic assignment methods on different road network scenarios may vary greatly. It is difficult for the reader to assess the quality of the results without prior knowledge about the difficulty of the road network. In the current work, we propose an approximate metric to characterise the difficulty of network scenarios which takes travellers’ origins and destinations as well as link capacities into account rather than relying on the size of the network. As this metric considers number of overlapping routes between the origins and destinations of the travelles, a higher number in the metric would indicate a higher possibility of congestion in the road network scenario.


Traffic Assignment Evolutionary Optimisation Network Complexity Experimental Evaluation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bazzan, A.L., Klügl, F.: Re-routing Agents in an Abstract Traffic Scenario (2008)Google Scholar
  2. 2.
    Zhu, S., Levinson, D., Zhang, L.: An agent-based route choice model. Working Papers 000089, University of Minnesota: Nexus Research Group (2007)Google Scholar
  3. 3.
    Sadek, A.W., Smith, B.L., Demetsky, M.J.: Dynamic traffic assignment: Genetic algorithms approach. Transportation Research Record: Journal of the Transportation Research Board 1588, 95–103 (1997)CrossRefGoogle Scholar
  4. 4.
    Cruz, F., van Woensel, T., Smith, J.M., Lieckens, K.: On the system optimum of traffic assignment in state-dependent queueing networks. European Journal of Operational Research 201(1), 183–193 (2010)CrossRefzbMATHGoogle Scholar
  5. 5.
    D’Acierno, L., Montella, B., De Lucia, F.: A stochastic traffic assignment algorithm based on ant colony optimisation. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 25–36. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    de Dios Ortuzar, J., Willumsen, L.G.: Modelling Transport, 2nd edn. John Willey & Sons (1994)Google Scholar
  7. 7.
    Fricker, J.D., Whitford, R.K.: Fundamentals of transportation engineering: a multimodal approach. Pearson Prentice Hall, Upper Saddle River (2004)Google Scholar
  8. 8.
    Bazzan, A.L.: Traffic as a Complex System: Four Challenges for Computer Science and Engineering (2007)Google Scholar
  9. 9.
    Chen, O., Ben-Akiva, M.: Game-Theoretic Formulations of Interaction Between Dynamic Traffic Control and Dynamic Traffic Assignment. Transportation Research Record: Journal of the Transportation Research Board 1617(-1), 179–188 (1998)CrossRefGoogle Scholar
  10. 10.
    Kitamura, R., Nakayama, S.: Can travel time information influence network flow? - Implications of the minority game. Transportation Research Record, 14–20 (2007)Google Scholar
  11. 11.
    Challet, D., Zhang, Y.C.: Emergence of cooperation and organization in an evolutionary game. Physica A 246(3-4), 12 (1997)CrossRefGoogle Scholar
  12. 12.
    Galib, S.M., Moser, I.: Road traffic optimisation using an evolutionary game (2011)Google Scholar
  13. 13.
    Dehmer, M., Barbarini, N., Varmuza, K., Graber, A.: A Large Scale Analysis of Information-Theoretic Network Complexity Measures Using Chemical Structures. PLoS ONE 4(12), e8057 (2009)Google Scholar
  14. 14.
    Strogatz, S.H.: Exploring complex networks. Nature 410(6825), 268–276 (2001)CrossRefGoogle Scholar
  15. 15.
    Constantine, G.: Graph complexity and the laplacian matrix in blocked experiments. Linear and Multilinear Algebra 28, 8 (1990)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Jukna, S.: On graph complexity. Combinatorics, Probability and Computing 15, 22 (2006)MathSciNetGoogle Scholar
  17. 17.
    Kim, J., Wilhelm, T.: What is a complex graph? Physica A: Statistical Mechanics and its Applications 387(11), 2637–2652 (2008)MathSciNetCrossRefGoogle Scholar
  18. 18.
    da F. Costa, L., Rodrigues, F., Travieso, G.: Characterization of complex networks: A survey of measurements. Advances in Physics 56(1), 76 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Syed Galib
    • 1
  • Irene Moser
    • 1
  1. 1.Swinburne University of TechnologyMelbourneAustralia

Personalised recommendations