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Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic
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DOI：10.1007/978-3-032-04774-8_87.png)
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Abstract
En 中文
Renewing and upgrading infrastructure is crucial for addressing societal, technological, and environmental challenges. Yet, such interventions can temporarily disrupt infrastructure availability, causing ripple effects on interconnected networks. This can alter user and stakeholder behavior, impacting demand and performance. In transportation, unavailable routes can increase costs, prompting alternative choices. Unfortunately, infrastructure agencies often neglect the behavioral aspects and uncertainty of freight forwarders' mode choice. To address this, a fuzzy logic approach is proposed to model mode choice in an agent-based simulation. Fuzzy logic accommodates imprecise data and subjective uncertainties in decision-making. Demonstrated in a Dutch multi-modal freight network case study, this model reveals how interventions affect mode choice and demand shifts. It offers valuable insights for infrastructure managers, aiding demand and performance estimation. Levers can be evaluated for their potential to promote modal shifts, enhancing environmental, functional, and safety aspects of transport networks.
Keywords:
Agent-based model
Fuzzy Logic
Infrastructure performance
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