Pavement Management: Inspection and Life-Cycle Assessment

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Infrastructures Inspection and Maintenance".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 3291

Special Issue Editors


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Guest Editor
Construction Project Management Research Group, Universitat Politècnica de València, Valencia, Spain
Interests: pavement maintenance; pavement management systems; life-cycle analysis; environmental sustainability; social sustainability; optimization; metaheuristics; decision-making; bridge design; structural optimization; construction principles
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Construction Project Management Research Group, Universitat Politècnica de València, Valencia, Spain
Interests: monitoring; material design; life-cycle analysis; environmental sustainability; social sustainability; pavement maintenance; pavement management systems; project management; lean construction; decision-making; construction principles

Special Issue Information

Dear Colleagues,

The pavement network is one of the largest heritage assets in a country. Its management is essential to maintain the network in a good condition and reduce transport costs and emissions. Pavement Management Systems (PMSs) are used to provide effective and efficient directives to allocate resources ensuring good pavement conditions and reducing life-cycle costs.  One of the main steps of a PMS is the inspection to determine the pavement condition. For this purpose, different devices and methods are used to collect and analyse data. In addition, a PMS uses this data to evaluate the deterioration over an analysis period and define more effective management plans that may address sustainability strategies. This Special Issue is seeking papers that explore new ways of inspection and life-cycle assessment of pavements that reduce the life-cycle cost and environmental impact and promote social progress. These objectives include, but are not limited to:

  • The development of technologies for automated inspection
  • Artificial Intelligence applied to pavement assessment
  • Pavement performance
  • Techniques to PMS
  • Life-cycle assessment
  • Economic, environmental, and social impact of pavement maintenance
  • Multi-objective optimization
  • Decision-making to integrate sustainable criteria

Dr. Tatiana García-Segura
Dr. Laura Montalbán-Domingo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Pavement
  • Maintenance
  • Management
  • Inspection
  • Life-cycle assessment
  • Sustainability
  • Decision-making
  • Artificial Intelligence

Published Papers (1 paper)

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Research

17 pages, 3912 KiB  
Article
Use of Deep Learning to Study Modeling Deterioration of Pavements a Case Study in Iowa
by Seyed Amirhossein Hosseini, Ahmad Alhasan and Omar Smadi
Infrastructures 2020, 5(11), 95; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5110095 - 05 Nov 2020
Cited by 20 | Viewed by 2678
Abstract
This paper describes the process and outcome of deterioration modeling for three different pavement types (asphalt, concrete, and composite) in the state of Iowa. Pavement condition data is collected by the Iowa Department of Transportation (DOT) and stored in a Pavement-Management Information System [...] Read more.
This paper describes the process and outcome of deterioration modeling for three different pavement types (asphalt, concrete, and composite) in the state of Iowa. Pavement condition data is collected by the Iowa Department of Transportation (DOT) and stored in a Pavement-Management Information System (PMIS). In the state of Iowa, the overall pavement condition is quantified using the Pavement Condition Index (PCI), which is a weighted average of indices representing different types of distress, roughness, and deflection. Deterioration models of PCI as a function of time were developed for the different pavement types using two modeling approaches. The first approach is the long/short-term memory (LSTM), a subset of a recurrent neural network. The second approach, used by the Iowa DOT, is developing individual regression models for each section of the different pavement types. A comparison is made between the two approaches to assess the accuracy of each model. The results show that the LSTM model achieved a higher prediction accuracy over time for all different pavement types. Full article
(This article belongs to the Special Issue Pavement Management: Inspection and Life-Cycle Assessment)
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