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 |
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Journal | Transportation Research Procedia |
Volume | 72 |
Pages (from-to) | 4468-4475 |
ISSN | 2352-1457 |
DOIs | |
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 |
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Location | Lisbon Congress Center |
Country/Territory | Portugal |
City | Lisbon |
Period | 14/11/2022 → 17/11/2022 |
Internet address |
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)
Keywords
- Bayesian Believe Network
- Climate Change
- Pavement and Maintenance Strategies
- Risk Abessment
- Software Architecture
- Technology-Driven Decision Support System