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Self-Organised Routing for Road Networks

  • Holger Prothmann
  • Sven Tomforde
  • Johannes Lyda
  • Jürgen Branke
  • Jörg Hähner
  • Christian Müller-Schloer
  • Hartmut Schmeck
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7166)

Abstract

Increasing mobility and the resulting rising traffic demands cause serious problems in urban regions world-wide. Approaches to alleviate the negative effects of traffic include an improved control of traffic lights and the introduction of dynamic route guidance systems that take current conditions into account. One solution for the former aspect is Organic Traffic Control (OTC) which provides a self-organised and self-adaptive system founded on the principles of Organic Computing. Based on OTC, this paper introduces a novel concept to dynamic route guidance in urban road networks. Inspired by the well-known protocols Distance Vector Routing and Link State Routing from the Internet domain, the major goal of the route guidance mechanism is to increase the network’s robustness with respect to congested or blocked roads. The efficiency of the developed approach is demonstrated in a simulation-based evaluation that considers disturbed and undisturbed traffic conditions.

Keywords

dynamic route guidance traffic signal control observer/controller architecture 

References

  1. 1.
    Bielefeldt, C., Condie, H.: COSMOS – Congestion Management Strategies and Methods in Urban Sites. Final report, The MVA Consultancy (1999)Google Scholar
  2. 2.
    Branke, J., Mnif, M., Müller-Schloer, C., Prothmann, H., Richter, U., Rochner, F., Schmeck, H.: Organic Computing – Addressing complexity by controlled self-organization. In: Margaria, T., Philippou, A., Steffen, B. (eds.) Proc. 2nd Int. Symp. on Leveraging Applications of Formal Methods, Verification and Validation (ISoLA 2006), pp. 200–206 (2006)Google Scholar
  3. 3.
    Casas, J., Ferrer, J.L., Garcia, D., Perarnau, J., Torday, A.: Traffic Simulation with Aimsun. In: Barceló, J. (ed.) Fundamentals of Traffic Simulation, pp. 173–232. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Emmerink, R.H.M., Nijkamp, P., Rietveld, P., Van Ommeren, J.N.: Variable message signs and radio traffic information: An integrated empirical analysis of drivers’ route choice behaviour. Transportation Research Part A: Policy and Practice 30(2), 135–153 (1996)CrossRefGoogle Scholar
  5. 5.
    Erke, A., Sagberg, F., Hagman, R.: Effects of route guidance variable message signs (VMS) on driver behaviour. Transportation Research Part F: Traffic Psychology and Behaviour 10(6), 447–457 (2007)CrossRefGoogle Scholar
  6. 6.
    Klejnowski, L.: Design and implementation of an algorithm for the distributed detection of disturbances in traffic networks. Master’s thesis, Institut für Systems Engineering – System und Rechnerarchitektur, Leibniz Universität Hannover (2008)Google Scholar
  7. 7.
    Prothmann, H., Branke, J., Schmeck, H., Tomforde, S., Rochner, F., Hähner, J., Müller-Schloer, C.: Organic traffic light control for urban road networks. Int. Journal of Autonomous and Adaptive Communications Systems 2(3), 203–225 (2009)CrossRefGoogle Scholar
  8. 8.
    Schmeck, H.: Organic Computing – A new vision for distributed embedded systems. In: Proc. 8th IEEE Int. Symp. on Object-Oriented Real-Time Distributed Computing (ISORC 2005), pp. 201–203 (2005)Google Scholar
  9. 9.
    Schrank, D., Lomax, T.: The 2009 Urban Mobility Report. Tech. rep., Texas Transportation Institute (2009)Google Scholar
  10. 10.
    Tanenbaum, A.S.: Computer Networks, 4th edn. Pearson Education (2002)Google Scholar
  11. 11.
    Webster, F.V.: Traffic Signal Settings. Road Research Technical Paper No. 39, UK Road Research Laboratory, Dept. of Scientific and Industrial Research (1958)Google Scholar
  12. 12.
    Wedde, H.F., Lehnhoff, S., et al.: Highly dynamic and adaptive traffic congestion avoidance in real-time inspired by honey bee behavior. In: Holleczek, P., Vogel-Heuser, B. (eds.) Mobilität und Echtzeit – Fachtagung der GI-Fachgruppe Echtzeitsysteme, pp. 21–31. Springer, Heidelberg (2007)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Holger Prothmann
    • 1
  • Sven Tomforde
    • 2
  • Johannes Lyda
    • 2
  • Jürgen Branke
    • 3
  • Jörg Hähner
    • 2
  • Christian Müller-Schloer
    • 2
  • Hartmut Schmeck
    • 1
  1. 1.Institute AIFBKarlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.Institute of Systems EngineeringLeibniz Universität HannoverHannoverGermany
  3. 3.Warwick Business SchoolUniversity of WarwickCoventryUK

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