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Traffic Assignment Optimization Using Flow-Based Multi-maps

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Advances in Practical Applications of Agents, Multi-Agent Systems, and Cognitive Mimetics. The PAAMS Collection (PAAMS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13955))

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Abstract

Traffic Assignment is a commonly used method for traffic modeling under congestion conditions. Many of the existing approaches find approximate solutions to the user equilibrium and the system optimum in terms of global travel time, though they can be computationally expensive. Previous works have shown that usage of Traffic-Weighted Multi-Maps (TWM) may help to reduce congestion in a wide range of scenarios. In this paper, we use TWM for traffic flow routing near the system optimum with an efficient computational performance. TWM is created using the k-shortest paths for the flows, and genetic algorithms are used to find the best TWM distribution for the flow paths to minimize global travel time (system optimum). The approach is illustrated with a non-trivial use case over a synthetic traffic network. Experimental results show that the TWM approach delivers efficient traffic routing, achieving low travel times under congestion conditions.

This work has been supported by Catedra Masmovil for Advanced Network Engineering and Digital Services (MANEDS) at Universidad de Alcala, CATEDRA2022-005.

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Author information

Authors and Affiliations

  1. Universidad de Alcala, Madrid, Spain

    Alvaro Paricio-Garcia & Miguel A. Lopez-Carmona

Authors
  1. Alvaro Paricio-Garcia
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  2. Miguel A. Lopez-Carmona
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Corresponding author

Correspondence to Alvaro Paricio-Garcia .

Editor information

Editors and Affiliations

  1. University of Lille, Lille, France

    Philippe Mathieu

  2. Umeå University, Umeå, Sweden

    Frank Dignum

  3. Universidade do Minho, Braga, Portugal

    Paulo Novais

  4. University of Salamanca, Salamanca, Spain

    Fernando De la Prieta

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Paricio-Garcia, A., Lopez-Carmona, M.A. (2023). Traffic Assignment Optimization Using Flow-Based Multi-maps. In: Mathieu, P., Dignum, F., Novais, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Cognitive Mimetics. The PAAMS Collection. PAAMS 2023. Lecture Notes in Computer Science(), vol 13955. Springer, Cham. https://doi.org/10.1007/978-3-031-37616-0_20

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  • DOI: https://doi.org/10.1007/978-3-031-37616-0_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37615-3

  • Online ISBN: 978-3-031-37616-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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