Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic

Sander Mooren; Andreas Hartmann; Sahand Asgarpour

doi:10.1007/978-3-032-04774-8_87

Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic

Sander Mooren^*
, Andreas Hartmann
, Sahand Asgarpour

^*Corresponding author for this work

Market Dynamics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Downloads (Pure)

Abstract

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.

Original language	English
Title of host publication	Transport Transitions: Advancing Sustainable and Inclusive Mobility
Subtitle of host publication	Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure
Editors	Ciaran McNally, Páraic Carroll, Beatriz Martinez-Pastor, Bidisha Ghosh, Marina Efthymiou, Nikolaos Valantasis-Kanellos
Place of Publication	Cham, Switzerland
Publisher	Springer
Pages	599-604
Number of pages	6
Volume	5
ISBN (Electronic)	978-3-032-04774-8
ISBN (Print)	978-3-032-04773-1
DOIs	https://doi.org/10.1007/978-3-032-04774-8_87
Publication status	Published - 2026
Event	10th Transport Research Arena, TRA 2024: Transport Transitions: Advancing Sustainable and Inclusive Mobility - Dublin, Ireland Duration: 15 Apr 2024 → 18 Apr 2024 Conference number: 10

Publication series

Name	Lecture Notes in Mobility
Publisher	Springer
ISSN (Print)	2196-5544
ISSN (Electronic)	2196-5552

Conference

Conference	10th Transport Research Arena, TRA 2024
Abbreviated title	TRA 2024
Country/Territory	Ireland
City	Dublin
Period	15/04/24 → 18/04/24

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978-3-032-04774-8_87Final published version, 539 KBLicence: CC BY

Cite this

Mooren, S., Hartmann, A., & Asgarpour, S. (2026). Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic. In C. McNally, P. Carroll, B. Martinez-Pastor, B. Ghosh, M. Efthymiou, & N. Valantasis-Kanellos (Eds.), Transport Transitions: Advancing Sustainable and Inclusive Mobility: Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure (Vol. 5, pp. 599-604). (Lecture Notes in Mobility). Springer. https://doi.org/10.1007/978-3-032-04774-8_87

Mooren, Sander ; Hartmann, Andreas ; Asgarpour, Sahand. / Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic. Transport Transitions: Advancing Sustainable and Inclusive Mobility: Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure. editor / Ciaran McNally ; Páraic Carroll ; Beatriz Martinez-Pastor ; Bidisha Ghosh ; Marina Efthymiou ; Nikolaos Valantasis-Kanellos. Vol. 5 Cham, Switzerland : Springer, 2026. pp. 599-604 (Lecture Notes in Mobility).

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title = "Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic",

abstract = "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{\textquoteright} 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. ",

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Mooren, S , Hartmann, A & Asgarpour, S 2026, Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic. in C McNally, P Carroll, B Martinez-Pastor, B Ghosh, M Efthymiou & N Valantasis-Kanellos (eds), Transport Transitions: Advancing Sustainable and Inclusive Mobility: Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure. vol. 5, Lecture Notes in Mobility, Springer, Cham, Switzerland, pp. 599-604, 10th Transport Research Arena, TRA 2024, Dublin, Ireland, 15/04/24. https://doi.org/10.1007/978-3-032-04774-8_87

Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic. / Mooren, Sander ; Hartmann, Andreas; Asgarpour, Sahand.
Transport Transitions: Advancing Sustainable and Inclusive Mobility: Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure. ed. / Ciaran McNally; Páraic Carroll; Beatriz Martinez-Pastor; Bidisha Ghosh; Marina Efthymiou; Nikolaos Valantasis-Kanellos. Vol. 5 Cham, Switzerland: Springer, 2026. p. 599-604 (Lecture Notes in Mobility).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic

AU - Mooren, Sander

AU - Hartmann, Andreas

AU - Asgarpour, Sahand

N1 - Conference code: 10

PY - 2026

Y1 - 2026

N2 - 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.

AB - 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.

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SN - 978-3-032-04773-1

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T3 - Lecture Notes in Mobility

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BT - Transport Transitions: Advancing Sustainable and Inclusive Mobility

A2 - McNally, Ciaran

A2 - Carroll, Páraic

A2 - Martinez-Pastor, Beatriz

A2 - Ghosh, Bidisha

A2 - Efthymiou, Marina

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PB - Springer

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ER -

Mooren S , Hartmann A, Asgarpour S. Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic. In McNally C, Carroll P, Martinez-Pastor B, Ghosh B, Efthymiou M, Valantasis-Kanellos N, editors, Transport Transitions: Advancing Sustainable and Inclusive Mobility: Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland, Volume 5: Smart Resilient Infrastructure. Vol. 5. Cham, Switzerland: Springer. 2026. p. 599-604. (Lecture Notes in Mobility). Epub 2025 Oct 4. doi: 10.1007/978-3-032-04774-8_87

Identifying Infrastructure Demand and Performance Changes Through Agent-Based Modelling Using Fuzzy Logic

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