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Sustainable Transportation Infrastructure Management
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Sustainable Transportation Infrastructure Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (1 August 2024) | Viewed by 9744

Special Issue Editor

Dr. Qing Lu

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of South Florida, Tampa, USA
Interests: pavement engineering; infrastructure systems management

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the state-of-the-art research outcomes and state-of-the-practice case studies on sustainable transportation infrastructure management. The main objectives include: 1) to present the status and progress of the transportation community’s work to improve the sustainability of transportation infrastructure in system management; 2) to update the new concepts, models, methodologies, and performance criteria developed towards sustainable management of infrastructure facilities; and 3) to provide implications and suggestions for policy implementation and future research.

Because of material aging, frequent use, environmental change, and mismanagement, many existing transportation infrastructure facilities are deteriorating and becoming more vulnerable to catastrophic failure, particularly in extreme events such as hurricanes, earthquakes, and wildfires. On the other hand, the renewal and expansion of infrastructure continue to consume ever-dwindling natural resources and release emissions that deteriorate the environment. There are growing awareness and demand for a sustainable transportation infrastructure system in the sense that it not only provides the desired service to the public in a cost-effective way, but also relies less on nonrenewable resources and imposes less negative environmental impact. To achieve such a goal, the transportation infrastructure must be managed in an intelligent manner. In recent years, there have been active research and practice efforts towards sustainable transportation infrastructure management. Stakeholders in the transportation community are also supportive of sustainable management technologies, practices, and policies. The latest technical information in this aspect, therefore, has great value to both researchers and practitioners.

This Special Issue welcomes the latest research in management technologies and applications that provide promising and practical solutions to various challenges faced by the engineering communities in a broad context of sustainable transportation infrastructure. Research along this line includes, but is not limited to, sampling and inspection of transportation infrastructure facilities with new technologies (e.g., smart sensors, automated survey vehicles or devices); facility performance modeling that incorporates sustainability; algorithms that support the decision-making process for maintenance, rehabilitation, renewal, and expansion of transportation infrastructure towards long-term sustainability; case studies; or engineering applications that present promising results. In particular, due to the ongoing COVID-19 pandemic, people’s travel patterns have changed dramatically around the world, significantly impacting the performance of transportation infrastructure. Such impacts need to be understood and potentially considered in the management practice of transportation infrastructure systems in the near future.

Dr. Qing Lu
Guest Editor

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • transportation infrastructure
  • management
  • sustainability
  • performance modeling
  • maintenance and rehabilitation
  • optimization
  • decision-making
  • catastrophic failure

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Published Papers (3 papers)

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Research

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24 pages, 8201 KiB  
Article
Enhancing Sustainable Transportation Infrastructure Management: A High-Accuracy, FPGA-Based System for Emergency Vehicle Classification
by Pemila Mani, Pongiannan Rakkiya Goundar Komarasamy, Narayanamoorthi Rajamanickam, Mohammad Shorfuzzaman and Waleed Mohammed Abdelfattah
Sustainability 2024, 16(16), 6917; https://doi.org/10.3390/su16166917 - 12 Aug 2024
Cited by 2 | Viewed by 1794
Abstract
Traffic congestion is a prevalent problem in modern civilizations worldwide, affecting both large cities and smaller communities. Emergency vehicles tend to group tightly together in these crowded scenarios, often masking one another. For traffic surveillance systems tasked with maintaining order and executing laws, [...] Read more.
Traffic congestion is a prevalent problem in modern civilizations worldwide, affecting both large cities and smaller communities. Emergency vehicles tend to group tightly together in these crowded scenarios, often masking one another. For traffic surveillance systems tasked with maintaining order and executing laws, this poses serious difficulties. Recent developments in machine learning for image processing have significantly increased the accuracy and effectiveness of emergency vehicle classification (EVC) systems, especially when combined with specialized hardware accelerators. The widespread use of these technologies in safety and traffic management applications has led to more sustainable transportation infrastructure management. Vehicle classification has traditionally been carried out manually by specialists, which is a laborious and subjective procedure that depends largely on the expertise that is available. Furthermore, erroneous EVC might result in major problems with operation, highlighting the necessity for a more dependable, precise, and effective method of classifying vehicles. Although image processing for EVC involves a variety of machine learning techniques, the process is still labor intensive and time consuming because the techniques now in use frequently fail to appropriately capture each type of vehicle. In order to improve the sustainability of transportation infrastructure management, this article places a strong emphasis on the creation of a hardware system that is reliable and accurate for identifying emergency vehicles in intricate contexts. The ResNet50 model’s features are extracted by the suggested system utilizing a Field Programmable Gate Array (FPGA) and then optimized by a multi-objective genetic algorithm (MOGA). A CatBoost (CB) classifier is used to categorize automobiles based on these features. Overtaking the previous state-of-the-art accuracy of 98%, the ResNet50-MOP-CB network achieved a classification accuracy of 99.87% for four primary categories of emergency vehicles. In tests conducted on tablets, laptops, and smartphones, it demonstrated excellent accuracy, fast classification times, and robustness for real-world applications. On average, it took 0.9 nanoseconds for every image to be classified with a 96.65% accuracy rate. Full article
(This article belongs to the Special Issue Sustainable Transportation Infrastructure Management)
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16 pages, 1670 KiB  
Article
Truck Impact on Buried Water Pipes in Interdependent Water and Road Infrastructures
by Shihab Uddin, Qing Lu and Hung Nguyen
Sustainability 2021, 13(20), 11288; https://doi.org/10.3390/su132011288 - 13 Oct 2021
Cited by 6 | Viewed by 3803
Abstract
In the development of sustainable and resilient infrastructures to adapt to the rapidly changing natural and social environment, the complexity of the dependencies and interdependencies within critical infrastructure systems need to be fully understood, as they affect various components of risk and lead [...] Read more.
In the development of sustainable and resilient infrastructures to adapt to the rapidly changing natural and social environment, the complexity of the dependencies and interdependencies within critical infrastructure systems need to be fully understood, as they affect various components of risk and lead to cascading failures. Water and road infrastructures are highly co-located but often managed and maintained separately. One important aspect of their interdependence is the impact of vehicle loading on a road on underlying water pipes. The existing studies lack a comprehensive evaluation of this subject and do not consider possible critical failure scenarios. This study constructed finite element models to analyze the responses of buried water pipes to vehicle loads under an array of scenarios, including various loads, pipe materials, pipe dimensions, and possible extreme conditions, such as corrosion in pipes and a sinkhole under the pipe. The results showed negligible impact of heavy trucks on buried water pipes. The pipe deflection under a maximum allowable truck load in the worst condition was still within the allowable range specified in standards such as those from the American Water Works Association. This implies that the impact of heavy vehicles on water pipes may not need to be considered in the context of the interdependency between water and road infrastructures, which leads to a more unidirectional dependency between these two infrastructures. Full article
(This article belongs to the Special Issue Sustainable Transportation Infrastructure Management)
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Review

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25 pages, 2557 KiB  
Review
Pavement Inspection in Transport Infrastructures Using Unmanned Aerial Vehicles (UAVs)
by Ianca Feitosa, Bertha Santos and Pedro G. Almeida
Sustainability 2024, 16(5), 2207; https://doi.org/10.3390/su16052207 - 6 Mar 2024
Cited by 5 | Viewed by 2711
Abstract
The growing demand for the transportation of goods and people has led to an increasing reliance on transportation infrastructure, which, in turn, subjects the pavements to high traffic volumes. In order to maintain adequate service and safety standards for users, it is essential [...] Read more.
The growing demand for the transportation of goods and people has led to an increasing reliance on transportation infrastructure, which, in turn, subjects the pavements to high traffic volumes. In order to maintain adequate service and safety standards for users, it is essential to establish effective maintenance strategies that ensure the preservation of pavement conditions. As a result, emerging innovations in pavement surface inspection methods, surpassing traditional techniques in terms of inspection and data processing speed and accuracy, have garnered significant attention. One such groundbreaking innovation in inspection systems that has been tested and used in recent years to assess infrastructure condition is the use of unmanned aerial vehicles (UAVs). This study aims to present a critical open-access literature review on the use of UAVs in the inspection of transportation infrastructure pavement in order to assess the type of equipment used, the technology involved, applicability conditions, data processing, and future evolution. The analysis of relevant literature suggests that the integration of intelligent technologies substantially enhances the accuracy of data collection and the detection of pavement distress. Furthermore, it is evident that most applications and research efforts are oriented towards exploring image processing techniques for the creation of 3D pavement models and distress detection and classification. Full article
(This article belongs to the Special Issue Sustainable Transportation Infrastructure Management)
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