• DocumentCode
    188704
  • Title

    A Versatile Description Framework for Modeling Behaviors in Traffic Simulations

  • Author

    Bonhomme, Alexandre ; Mathieu, Philippe ; Picault, Sebastien

  • Author_Institution
    LIFL, Lille 1 Univ., Villeneuve d´Ascq, France
  • fYear
    2014
  • fDate
    10-12 Nov. 2014
  • Firstpage
    937
  • Lastpage
    944
  • Abstract
    Microscopic simulations of road traffic are a typical application domain for Multi-Agent Systems. Indeed, the individual-based approach allows to take into account the diversity of behaviors so as to consider real situations. More recently, geographical databases provide environmental information under open formats, which offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. The use of such data, together with the adaptability of MAS, allows the realization of decision support systems that are able to integrate environmental and behavioral modifications in a direct way, and compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and flows. We describe here a modeling approach and a comprehensive process which lead to the development of such a tool.
  • Keywords
    decision support systems; geographic information systems; multi-agent systems; road traffic; MAS; agent-based traffic simulators; decision support systems; environmental information; geographical databases; microscopic simulations; modeling behaviors; multiagent systems; road traffic simulations; traffic conditions; versatile description framework; Context; Data models; Educational institutions; Generators; Multi-agent systems; Roads; Vehicles; Multi-Agent Simulation; GIS; Road Traffic; Traffic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
  • Conference_Location
    Limassol
  • ISSN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2014.158
  • Filename
    6984578