Self-Organized Control of Irregular or Perturbed Network Traffic

  • Dirk HelbingEmail author
  • Stefan Lämmer
  • Jean-Patrick Lebacque
Part of the Advances in Computational Management Science book series (AICM, volume 7)


We present a fluid-dynamic model for the simulation of urban traffic networks with road sections of different lengths and capacities. The model allows one to efficiently simulate the transitions between free and congested traffic, taking into account congestion-responsive traffic assignment and adaptive traffic control. We observe dynamic traffic patterns which significantly depend on the respective network topology. Synchronization is only one interesting example and implies the emergence of green waves. In this connection, we will discuss adaptive strategies of traffic light control which can considerably improve throughputs and travel times, using self-organization principles based on local interactions between vehicles and traffic lights. Similar adaptive control principles can be applied to other queueing networks such as production systems. In fact, we suggest to turn push operation of traffic systems into pull operation: By removing vehicles as fast as possible from the network, queuing effects can be most efficiently avoided. The proposed control concept can utilize the cheap sensor technologies available in the future and leads to reasonable operation modes. It is flexible, adaptive, robust, and decentralized rather than based on precalculated signal plans and a vulnerable traffic control center.


Travel Time Arrival Rate Road Network Queue Length Green Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2005

Authors and Affiliations

  • Dirk Helbing
    • 1
    Email author
  • Stefan Lämmer
    • 1
  • Jean-Patrick Lebacque
    • 2
  1. 1.Dresden University of TechnologyGermany
  2. 2.Institut National de Recherche sur les Transports er leur Sécurité (INRETS)France

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