Simulating a Dynamic Transport System to Enhance the Transportation Performance in Road Crisis Condition

  • Daniel de Oliveira
  • Mirian Buss Gonçalves
  • Edson Tadeu Bez
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 275)


This paper studies the effects of the real-time information about transport network conditions as a key for constructing routes in an Advanced Travelers Information System in terms of traveled distance. It does so by an experiment that aims to simulate an ordinary transport logistics operation given by a set of 2 synthetic scenarios, where interruption events were randomly generated over the transport network. The results found were analyzed as well as compared to the no interruptions benchmark scenario. It has shown that if there was information available for all road users it would result in best route decisions and consequently would save resources for the whole transport system.


Dynamic Transport Network ITS Transport Simulation Transport Crisis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Klein, B., Lopez-de-Ipina, D., Guggenmos, C., Velasco, J.P.: User-Aware Location Management of Prosumed Micro-services. Interact. Comput. (2013)Google Scholar
  2. 2.
    Novaes, A.G.N., Frazzon, E.M., Burin, P.J.: Dynamic Vehicle Routing in Overcongested Urban Areas. In: Proceedings of Second International Conference on Dynamics in Logistics, LDIC 2009, pp. 103–112 (2009)Google Scholar
  3. 3.
    Slinn, M., Matthews, P., Guest, P.: Intelligent Transport Systems. Traffic Engineering Design: Principles and Practice. Elsevier (2005)Google Scholar
  4. 4.
    Garrett, A.: Intelligent transport systems - potential benefits and immediate issues. Road Transp. Res. 7, 61–69 (1998)Google Scholar
  5. 5.
    Jarašũniene, A.: Research into Intelligent Transport Systems (ITS) technologies and efficiency. Transport 22, 61–67 (2007)Google Scholar
  6. 6.
    Jeffery, D.: Intelligent transport systems for traveller information. Highw. Transp. 46, 21–23 (1999)Google Scholar
  7. 7.
    Tsekeris, T., Tsekeris, C., Koskinas, K., Lavdas, M.: Intelligent transport systems and regional digital convergence in Greece. J. Transp. Lit. 7, 297–318 (2012)CrossRefGoogle Scholar
  8. 8.
    Adler, J.L., Blue, V.J.: Toward the design of intelligent traveler information systems. Transp. Res. Part C Emerg. Technol. 6, 157–172 (1998)CrossRefGoogle Scholar
  9. 9.
    Wahle, J., Annen, O., Schuster, C., Neubert, L., Schreckenberg, M.: A dynamic route guidance system based on real traffic data. Eur. J. Oper. Res. 131, 302–308 (2001)Google Scholar
  10. 10.
    Oliveira, D., Gonçalves, M.B., Bez, E.T.: Humanitarian Logistics: Developing a Dynamic Network for Road Transportation in Emergency Situations. Adv. Commun. Technol. (2014)Google Scholar
  11. 11.
    Sumiła, M.: Selected Aspects of Message Transmission Management in ITS Systems. In: Mikulski, J. (ed.) TST 2012. CCIS, vol. 329, pp. 141–147. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  12. 12.
    Chorus, C.G., Molin, E.J.E., Van Wee, B., Arentze, T.A., Timmermans, H.J.P.: Responses to Transit Information among Car-drivers: Regret-based Models and Simulations. Transp. Plan. Technol. 29, 249–271 (2006)CrossRefGoogle Scholar
  13. 13.
    Drozdek, A.: Data Structures and Algorithms in C++, 3rd edn. Cengage Learning (2005)Google Scholar
  14. 14.
    IBGE (Instituto Brasileiro de Geografia e Estatística),
  15. 15.
  16. 16.
    Robinson, S.: Simulation: The Practice of Model Development and Use. John Wiley & Sons, England (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Daniel de Oliveira
    • 1
  • Mirian Buss Gonçalves
    • 1
  • Edson Tadeu Bez
    • 2
  1. 1.Department of Production and Systems EngineeringFederal University of Santa CatarinaFlorianópolisBrazil
  2. 2.Department of Earth SciencesUniversity of Vale do ItajaíSão JoséBrazil

Personalised recommendations