To Adapt or Not to Adapt – Consequences of Adapting Driver and Traffic Light Agents

  • Ana L. C. Bazzan
  • Denise de Oliveira
  • Franziska Klügl
  • Kai Nagel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4865)


One way to cope with the increasing traffic demand is to integrate standard solutions with more intelligent control measures. However, the result of possible interferences between intelligent control or information provision tools and other components of the overall traffic system is not easily predictable. This paper discusses the effects of integrating co-adaptive decision-making regarding route choices (by drivers) and control measures (by traffic lights). The motivation behind this is that optimization of traffic light control is starting to be integrated with navigation support for drivers. We use microscopic, agent-based modelling and simulation, in opposition to the classical network analysis, as this work focuses on the effect of local adaptation. In a scenario that exhibits features comparable to real-world networks, we evaluate different types of adaptation by drivers and by traffic lights, based on local perceptions. In order to compare the performance, we have also used a global level optimization method based on genetic algorithms.


Travel Time Multiagent System Autonomous Agent Route Choice Average Travel 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-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ana L. C. Bazzan
    • 1
  • Denise de Oliveira
    • 1
  • Franziska Klügl
    • 2
  • Kai Nagel
    • 3
  1. 1.Instituto de Informática, UFRGS, Caixa Postal 15064, 91.501-970  Porto Alegre, RSBrazil
  2. 2.Dep. of Artificial IntelligenceUniversity of WürzburgWürzburgGermany
  3. 3.Inst. for Land and Sea Transport SystemsTU BerlinBerlinGermany

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