Simulation model of traffic in smart cities for decision-making support: Case study in tudela (Navarre, Spain)

  1. Latorre-Biel, J.-I. 1
  2. Faulin, J. 1
  3. Jiménez, E. 2
  4. Juan, A.A. 3
  1. 1 Universidad Pública de Navarra
    info

    Universidad Pública de Navarra

    Pamplona, España

    ROR https://ror.org/02z0cah89

  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  3. 3 Universitat Oberta de Catalunya
    info

    Universitat Oberta de Catalunya

    Barcelona, España

    ROR https://ror.org/01f5wp925

Revista:
Lecture Notes in Computer Science

ISSN: 0302-9743

Año de publicación: 2017

Volumen: 10268 LNCS

Páginas: 144-153

Tipo: Artículo

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DOI: 10.1007/978-3-319-59513-9_15 SCOPUS: 2-s2.0-85020875678 GOOGLE SCHOLAR

Otras publicaciones en: Lecture Notes in Computer Science

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Resumen

Traffic constitutes a key factor in a city. Thus, city layout, quality of services, pollution, products delivery, people transportation, and many other activities depend closely on traffic. The decision makers of a smart city should conceive ways for limiting pollution, fuel consumption, and transportation times, as well as accidents and disturbances to dwellers, to give a few examples. In order to achieve these objectives, decisions should be made on the appropriate configuration of the reachable degrees of freedom of the traffic system. However, the complexity of traffic systems, and the conflicting goals of the decision makers in a smart city, makes decision support systems a tool to be considered. In this paper one of such systems is described. It is based on the use of a simulation model for supporting the decision making by what-if experiments or by optimization. This model is developed using the paradigm of the Petri nets and is applicable for simulation and for structural analysis. The model is simple and can be easily adapted to different cities or road networks by adding to the model the layout of the city streets and roads, as well as some additional information such as traffic lights or number and type of vehicles. © Springer International Publishing AG 2017.