Combining Macro-level and Agent-based Modeling for Improved Freight Transport Analysis

Macro-level models is the dominating type of freight transport analysis models for supporting the decision-making in public authorities. Recently, also agent-based models have been used for this purpose. These two model types have complementing characteristics: macro-level models enable to study large geographic regions in low level of detail, whereas agent-based models enable to study entities in high level of detail, but typically in smaller regions. In this paper, the authors suggest and discuss three approaches for combining macro-level and agent-based modeling: exchanging data between models, conducting supplementary sub-studies, and integrating macro-level and agent-based modeling. They partly evaluate these approaches using two case studies and by elaborating on existing freight transport analysis approaches based on executing models in sequence.

Language

  • English

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Filing Info

  • Accession Number: 01536559
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 30 2014 3:14PM