Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM): focus on risk abessment framework for climate change adaptation

Shahrzad M. Pour; Amir M. Masoumi; Niels Skov Dujardin

doi:10.1016/j.trpro.2023.11.297

Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM): focus on risk abessment framework for climate change adaptation

Shahrzad M. Pour^*
, Amir M. Masoumi
, Niels Skov Dujardin

^*Corresponding author for this work

Danish Road Directorate

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

Decision Support Systems for pavement and maintenance strategies have traditionally been designed as silos led to local optimum systems. Moreover, since big data usage didn't exist as result of Industry 4.0 as of today, DSSs were not initially designed adaptive to the sources of uncertainties led to rigid decisions. Motivated by the vulnerability of the road abets to the climate phenomena, this paper takes a visionary step towards introducing a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance activities called TDADSS-IPM. As part of such DSS, a bottom-up risk abessment model is met via Bayesian Belief Networks (BBN) to realize the actual condition of the Danish roads due to weather condition. Such model fills the gaps in the knowledge domain and develops a platform that can be trained over time, and applied in real-time to the actual event.

Original language	English
Journal	Transportation Research Procedia
Volume	72
Pages (from-to)	4468-4475
ISSN	2352-1457
DOIs	https://doi.org/10.1016/j.trpro.2023.11.297
Publication status	Published - 2023
Event	Transport Research Arena 2022 - Lisbon Congress Center, Lisbon, Portugal Duration: 14 Nov 2022 → 17 Nov 2022 https://traconference.eu/ https://traconference.eu

Conference

Conference	Transport Research Arena 2022
Location	Lisbon Congress Center
Country/Territory	Portugal
City	Lisbon
Period	14/11/2022 → 17/11/2022
Internet address	https://traconference.eu/ https://traconference.eu

Bibliographical note

Publisher Copyright:
© 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Bayesian Believe Network
Climate Change
Pavement and Maintenance Strategies
Risk Abessment
Software Architecture
Technology-Driven Decision Support System

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10.1016/j.trpro.2023.11.297

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Cite this

@inproceedings{8f156ac509a24da6b59b07cbc5e1aa46,

title = "Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM): focus on risk abessment framework for climate change adaptation",

abstract = "Decision Support Systems for pavement and maintenance strategies have traditionally been designed as silos led to local optimum systems. Moreover, since big data usage didn't exist as result of Industry 4.0 as of today, DSSs were not initially designed adaptive to the sources of uncertainties led to rigid decisions. Motivated by the vulnerability of the road abets to the climate phenomena, this paper takes a visionary step towards introducing a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance activities called TDADSS-IPM. As part of such DSS, a bottom-up risk abessment model is met via Bayesian Belief Networks (BBN) to realize the actual condition of the Danish roads due to weather condition. Such model fills the gaps in the knowledge domain and develops a platform that can be trained over time, and applied in real-time to the actual event.",

keywords = "Bayesian Believe Network, Climate Change, Pavement and Maintenance Strategies, Risk Abessment, Software Architecture, Technology-Driven Decision Support System",

author = "Pour, \{Shahrzad M.\} and Masoumi, \{Amir M.\} and Dujardin, \{Niels Skov\}",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0); Transport Research Arena 2022<br/>, TRA2022 ; Conference date: 14-11-2022 Through 17-11-2022",

year = "2023",

doi = "10.1016/j.trpro.2023.11.297",

language = "English",

volume = "72",

pages = "4468--4475",

journal = "Transportation Research Procedia",

issn = "2352-1457",

publisher = "Elsevier",

url = "https://traconference.eu/, https://traconference.eu",

}

Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM): focus on risk abessment framework for climate change adaptation. / Pour, Shahrzad M.; Masoumi, Amir M.; Dujardin, Niels Skov.
In: Transportation Research Procedia, Vol. 72, 2023, p. 4468-4475.

Research output: Contribution to journal › Conference article › Research › peer-review

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T1 - Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM)

T2 - Transport Research Arena 2022<br/>

AU - Pour, Shahrzad M.

AU - Masoumi, Amir M.

AU - Dujardin, Niels Skov

PY - 2023

Y1 - 2023

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AB - Decision Support Systems for pavement and maintenance strategies have traditionally been designed as silos led to local optimum systems. Moreover, since big data usage didn't exist as result of Industry 4.0 as of today, DSSs were not initially designed adaptive to the sources of uncertainties led to rigid decisions. Motivated by the vulnerability of the road abets to the climate phenomena, this paper takes a visionary step towards introducing a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance activities called TDADSS-IPM. As part of such DSS, a bottom-up risk abessment model is met via Bayesian Belief Networks (BBN) to realize the actual condition of the Danish roads due to weather condition. Such model fills the gaps in the knowledge domain and develops a platform that can be trained over time, and applied in real-time to the actual event.

KW - Bayesian Believe Network

KW - Climate Change

KW - Pavement and Maintenance Strategies

KW - Risk Abessment

KW - Software Architecture

KW - Technology-Driven Decision Support System

U2 - 10.1016/j.trpro.2023.11.297

DO - 10.1016/j.trpro.2023.11.297

M3 - Conference article

AN - SCOPUS:85182929434

SN - 2352-1457

VL - 72

SP - 4468

EP - 4475

JO - Transportation Research Procedia

JF - Transportation Research Procedia

Y2 - 14 November 2022 through 17 November 2022

ER -

Towards a Technology-Driven Adaptive Decision Support System for Integrated Pavement and Maintenance strategies (TDADSS-IPM): focus on risk abessment framework for climate change adaptation

Abstract

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this