A Routine and Post-disaster Road Corridor Monitoring Framework for the Increased Resilience of Road Infrastructures

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Abstract

Resilient road infrastructures are vital to a society's welfare and economy; however, monitoring and maintaining them is becoming increasingly complex due to climate change, ageing infrastructure assets and increased traffic loads. Increasing maintenance expenditure is required to refurbish assets, of which the majority are already reaching the end of their predicted service life, and to make them resilient against (future) stressors that lead to accelerated degradation and damage. Monitoring is crucial in assessing the state and performance level of infrastructures. However, most Western countries have deferred essential maintenance and monitoring. Catastrophic events in recent years have highlighted the state of today's crumbling infrastructure and made it evident that most countries face the critical challenge of upkeeping these vital “lifelines”. There is a need for improved, automated, accurate and synoptic monitoring technologies to support road operators in keeping road infrastructures safe and functional in routine and emergency scenarios. Modern inspection technology increasingly supports human-based inspections and is extremely valuable in alleviating the limitations that exist in operational or traditional monitoring methods. There are various state-of-the-art technologies and perspectives from which infrastructure monitoring can be regarded. This dissertation considers it in a non-destructive and remote sensing manner while simultaneously meeting the demand of road operators to achieve monitoring in a real-time, multi-objective and automatic manner. To this end, research was conducted to investigate and propose novel monitoring technology to aid road infrastructure monitoring in routine and emergency scenarios using earth observation platforms and Artificial Intelligence (AI).

The following objectives were investigated:
-To determine the applicability of anomaly-detecting generative adversarial networks (ADGANs) for routine and post-disaster damage assessments. (Chapters 2 and 3)
-To develop a framework for real-time infrastructure monitoring using (hybrid) UAVs. (Chapter 4)
-To provide road operators with qualitative high-level information products to detect anomalous infrastructure scenarios from a UAV platform. (Chapter 5)
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
  • Faculty of Geo-Information Science and Earth Observation
Supervisors/Advisors
  • Kerle, Norman, Supervisor
  • Vosselman, George, Supervisor
  • Nex, Francesco, Supervisor
Award date13 Sept 2023
Publisher
Print ISBNs978-90-365-5710-8
DOIs
Publication statusPublished - 13 Sept 2023

Keywords

  • Edge computing
  • Artificial intelligence
  • Road infrastructure
  • Generative Adversarial Networks
  • Anomaly detection
  • Degradation
  • Damage
  • infrastructure monitoring
  • Post-disaster
  • xBD
  • Building damage detection
  • satellite
  • Unmanned Aerial Vehicle (UAV)
  • Real-Time
  • remote processing
  • fixed-wing VTOL
  • hybrid UAV

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