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Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems

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

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 28262

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Special Issue Editors

Dr. Francesco Abbondati

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Guest Editor

Engineering Department, University of Napoli Parthenope, 80143 Napoli, Italy
Interests: roads; railways; airports; infrastructures building materials

Prof. Dr. Luigi Pariota

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Guest Editor

Civil Building and Environmental Department, University of Napoli Federico II, 80125 Napoli, Italy
Interests: transport management; intelligent transportation systems; cooperative connected automated mobility
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Special Issue Information

Dear Colleagues,

Sustainable Engineering Development for Transport Infrastructures and Systems describes transport infrastructures design and maintenance, and systems of transport planning and operations, which are consistent with wider concerns of sustainability, and sustainable transportation system. The European Union Council of Ministers of Transport defines a sustainable transportation system as one that:

Allows the basic access and development needs of individuals, companies and society to be met safely and in a manner consistent with human and ecosystem health, and promotes equity within and between successive generations.
Is affordable, operates fairly and efficiently, offers a choice of transport mode, and supports a competitive economy, as well as balanced regional development.
Limits emissions and waste within the planet's ability to absorb them, uses renewable resources at or below their rates of generation and uses non-renewable resources at or below the rates of development of renewable substitutes, while minimizing the impact on the use of land and the generation of noise.
Sustainability extends beyond just the operating efficiency and emissions. A life-cycle assessment involves production, use and post-use considerations.

The United Nations in 2015 adopted 17 Sustainable Development Goals (SDGs), also known as the Global Goals, as a universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity.

Various SDGs could be related to sustainable transport. These include SDG 3 on health (increased road safety), SDG 7 on energy, SDG 8 on decent work and economic growth, SDG 9 on resilient infrastructure, SDG 11 on sustainable cities (access to transport and expanded public transport), SDG 12 on sustainable consumption and production (ending fossil fuel subsidies) and SDG 14 on oceans, seas and marine resources.

More recently approved 2020, the European Green Deal is a set of policies proposed by the European Commission with the overall goal of achieving climate neutrality in Europe by 2050. The policy area of “Sustainable Industry” includes boosting the modern aspects of industries, influencing the exploration and creation of climate neutral circular economy friendly goods markets; a ‘sustainable products’ policy will focus on reducing the wastage of materials to ensure products will be reused and recycling processes will be reinforced. The policy area of “Building and renovation” focuses on promoting the use of energy efficient methods, and on increasing digitalisation.

The main purpose of this Special Issue is to collect recent contributions in this wide field in terms of both new ideas and emerging trends, actual quantification of actuated interventions, and tested solutions effects.

Dr. Francesco Abbondati
Prof. Dr. Luigi Pariota
Guest Editors

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Keywords

sustainable transport infrastructures
road materials
railway materials
airport materials
environmental impact
sustainable pavements
life cycle assessment
end of waste
circular economy
ecological transition
raw material reduction
secondary raw materials
polluting emissions reduction
material selection
preservation strategies
reclaimed asphalt pavements
modified asphalt pavements
polymer modified binders
best available techniques
green public procurement
minimum environmental criteria
European green deal
smart roads
infrastructure building information modeling
transportation safety
maintenance strategies
transport and social sustainability
policies and governance
tools and incentives
clean fuels and vehicles
electric vehicles
hybrid vehicles
hydrogen vehicles
car restricted zones/living streets
traffic calming/speed reduction
integrated pricing strategies
congestion pricing
accessible transport systems
bus services
demand responsive transport
public transport
quality of service
rail transport
bike-sharing
list of bicycle-sharing systems
carpooling
car sharing
cycling
transport management
transit-oriented development
transportation demand management
sustainable freight transport

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Published Papers (10 papers)

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Research

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15 pages, 2788 KiB

Open AccessArticle

Laboratory Investigation and Machine Learning Modeling of Road Pavement Asphalt Mixtures Prepared with Construction and Demolition Waste and RAP

by Fabio Rondinella, Cristina Oreto, Francesco Abbondati and Nicola Baldo

Sustainability 2023, 15(23), 16337; https://doi.org/10.3390/su152316337 - 27 Nov 2023

Cited by 4 | Viewed by 1426

Abstract

Due to the decreasing availability of virgin materials coupled with an increased awareness of environmental sustainability issues, many researchers have focused their efforts on investigating innovative technological solutions in the civil engineering domain. This paper aims to evaluate the suitability of construction and demolition waste (C and DW) and reclaimed asphalt pavement (RAP) reused within asphalt mixtures (AMs) prepared for the binder layer of road pavements. Both hot and cold mixing methodologies were investigated. The technical assessment was based on the volumetric and mechanical suitability, according to saturated surface dry voids (SSDV) and indirect tensile strength (ITS) tests carried out at 10 °C, respectively. Laboratory findings showed that all the hot AMs matched the desired target SSDV at the design gyrations number at different optimum bitumen content levels, alternatively showing a non-significant variation or a significant increase in ITS compared to conventional hot mix asphalt. Conversely, the cold AMs with cement and emulsion bitumen showed a greater volume of voids and moisture sensitivity, and lower temperature susceptibility compared to hot AMs, reaching, on average, 11% lower ITS when using coarse C and DW aggregates and 43% lower ITS when using filler from C and DW. These volumetric and mechanical properties were modeled by means of support vector machines and categorical boosting (CatBoost) machine learning algorithms. The results proved to be satisfactory, with CatBoost determination coefficients R² referring to SSDV and ITS equal to 0.8678 and 0.9916, respectively. This allowed for the mechanical performance of these sustainable mixtures to be predicted with high accuracy and implemented within conventional mix design procedures. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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18 pages, 9052 KiB

Open AccessArticle

Research on Appearance Detection, Sorting, and Regrouping Technology of Retired Batteries for Electric Vehicles

by Fengdan Liu, Jiangyi Chen, Dongchen Qin and Tingting Wang

Sustainability 2023, 15(21), 15523; https://doi.org/10.3390/su152115523 - 1 Nov 2023

Viewed by 1312

Abstract

The rapid proliferation of electric vehicle adoption has brought about significant changes in energy consumption patterns, but improper disposal of retired batteries poses new challenges to the environment. In order to promote the sustainable development of the industry using retired batteries, this paper focuses on the research on retired battery appearance detection, sorting, and regrouping technologies. Firstly, the standards for retired battery appearance detection are analyzed, and a method of acquiring battery appearance features through two-stage image acquisition is proposed. Machine vision is employed to achieve the appearance filtering of retired batteries, overcoming the shortcomings of manual screening. For the filtered batteries, capacity, internal resistance, and open-circuit voltage are determined as indicators. Analytic hierarchy process and Gray relation analysis are employed for classification based on four application scenarios. Additionally, an improved Gaussian mixture model clustering algorithm is proposed. In the recombination process, the algorithm parameters are adaptively adjusted for each battery category. Experimental results demonstrate that the accuracy of battery appearance filtering exceeds 97%, and the improved algorithm effectively enhances the consistency among batteries. Compared to the baseline algorithm, the performance consistency of regrouping batteries is increased by more than 5%. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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16 pages, 2810 KiB

Open AccessArticle

Life Cycle Analysis of an On-the-Road Modular Vehicle Concept

by Christian Ulrich, Mario Feinauer, Katharina Bieber, Stephan A. Schmid and Horst E. Friedrich

Sustainability 2023, 15(13), 10303; https://doi.org/10.3390/su151310303 - 29 Jun 2023

Cited by 1 | Viewed by 1453

Abstract

In order to reduce the environmental impacts caused by the transport sector, autonomous and electrified on-the-road modular vehicles (otrm) could be a solution. By separating the drive unit from the transport unit, they enable use cases for various transport tasks and reduce individual and motorized transport and its generated emissions. Therefore, the goal of this study is to assess the environmental impacts from cradle to grave by applying the LCA methodology for a defined otrm—the U-Shift—vehicle fleet considering a specific use case relative to a reference vehicle fleet. The results indicate that the U-Shift fleet reduces the life cycle environmental impacts in a range of 3–28% for all of the seven impact categories, which are analyzed in detail. While emissions from the use phase are similar, U-Shift has an environmental benefit in the production phase due to a low amount of resource-intensive driveboards. Considering the early development stage of U-Shift, several measures are discussed, addressing the material and configuration aspects of the vehicles as well as optimized use case applications, which promise further impact-reduction potential. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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17 pages, 8048 KiB

Open AccessArticle

Implementation of Magnetic Markers for the Diagnostics of Conveyor Belt Transportation Systems

by Karol Semrád and Katarína Draganová

Sustainability 2023, 15(11), 8705; https://doi.org/10.3390/su15118705 - 28 May 2023

Cited by 2 | Viewed by 2038

Abstract

Together with the research and development of belt conveyors, diagnostic methods for their reliable operation have been developed. Our research is focused on the development of a diagnostic system and method of sensing the magnetic markers implemented directly into the conveyor belt, as in this way, it is possible to determine the velocity of the conveyor belt, which can be a source of information about the potential malfunction of the drive unit, control system, or of the belt itself. The magnetic markers can be also used to mark the particular segments of the conveyor belt, which can significantly enhance maintenance procedures thanks to the identification of damaged segments and the possibility to stop the conveyor belt in the maintenance area. However, problems can occur with the implementation of the magnetic markers. To prevent the magnetic markers from falling out, FEM (finite element method) simulations and analyses of commercially available magnetic markers with different dimensions were performed to analyze the nominal and friction force and related average contact pressure acting on the magnetic markers implemented into holes drilled into the conveyor belt in the curved state when passing through the drum. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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22 pages, 2266 KiB

Open AccessArticle

Forecast of the Evolution Trend of Total Vehicle Sales and Power Structure of China under Different Scenarios

by Min Zhao, Yu Fang and Debao Dai

Sustainability 2023, 15(5), 3985; https://doi.org/10.3390/su15053985 - 22 Feb 2023

Cited by 1 | Viewed by 3464

Abstract

Accurate forecasting of the power structure and sales volume of the automobile industry is crucial for corporate decision making and national planning. Based on the auto sales data from 2011 to 2022 compiled from the official website of the China Association of Automobile Manufacturers (CAAM), the total auto sales in China from 2023 to 2030 were firstly predicted using a combined GM (1,1), and quadratic exponential smoothing forecast model optimized by particle swarm algorithm. Subsequently, the vehicles were classified into the following four categories by power: traditional fuel vehicles, pure electric vehicles, plug-in hybrid vehicles, and hydrogen fuel cell vehicles. Then, based on vehicle sales data from 2015 to 2022, The Markovian model and the component data model based on hyperspherical transformation are used to predict the vehicle power structure from 2023 to 2030 under the natural evolution scenario and the consumer purchase intention dominant scenario, respectively. The results show that total vehicle sales in China are expected to reach 32.529 million units by 2030. Under the natural evolution scenario and the consumer purchase intention dominant scenario, China will achieve the planned target of 40% of the new car market in the sales of new energy vehicles in 2028 and 2026, respectively. By 2030, under the natural evolution scenario, the sales volume of traditional fuel vehicles in the new car market will be 54.83%, the proportion of pure electric vehicles will be 35.92%, the proportion of plug-in hybrid vehicles will be 9.23%, and the proportion of hydrogen fuel cell vehicles will be 0.02%. Under the consumer purchase intention dominant scenario, the proportions of the four power types are 36.51%, 48.11%, 15.28%, and 0.10%, respectively. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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30 pages, 10920 KiB

Open AccessArticle

Intelligent Assessment of Pavement Condition Indices Using Artificial Neural Networks

by Sami Abdullah Osman, Meshal Almoshaogeh, Arshad Jamal, Fawaz Alharbi, Abdulhamid Al Mojil and Muhammad Abubakar Dalhat

Sustainability 2023, 15(1), 561; https://doi.org/10.3390/su15010561 - 28 Dec 2022

Cited by 3 | Viewed by 2533

Abstract

The traditional manual approach of pavement condition evaluation is being replaced by more sophisticated automated vehicle systems. Although these automated systems have eased and hastened pavement management processes, research is ongoing to further improve their performances. An average state road agency handles thousands of kilometers of the road network, most of which have multiple lanes. Yet, for practical reasons, these automated systems are designed to evaluate road networks one lane at a time. This requires time, energy, and possibly more equipment and manpower. Multiple Linear Regression (MLR) analysis and Artificial Neural Network (ANN) were employed to examine the feasibility of modeling and predicting pavement distresses of multiple lanes as functions of pavement distresses of a single adjacent lane. The successful implementation of this technique has the potential to cut the energy and time requirement at the condition evaluation stage by at least half, for a uniform multi-lane highway. Results showed promising model performances that indicate the possibility of evaluating a multi-lane highway pavement condition (PC) by single lane inspection. Traffic direction parameters, location, and lane matching parameters contributed significantly to the performance of the ANN PC prediction models. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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10 pages, 258 KiB

Open AccessArticle

Proposal for an Institutional Carpooling System among Workers from the Public-Education Sector

by María del Carmen Rey-Merchán, Antonio López-Arquillos, Manuela Pires Rosa and Jesús Manuel Gómez-de-Gabriel

Sustainability 2022, 14(21), 14601; https://doi.org/10.3390/su142114601 - 7 Nov 2022

Cited by 1 | Viewed by 2785

Abstract

Car journeys to work represent a high percentage of daily mobility. Carpooling can be an efficient alternative for managing this transport demand. Carpooling benefits are not limited to reducing emissions and energy consumption: users can also benefit in the reduction in travel costs and travel time using high-occupancy vehicle lanes, as well as reducing commuting stress. The organization of such a system is not easy to carry out individually. Institutions and companies with a high number of employees are suitable for carpooling initiatives, and the education sector holds a high number of workers. Considering the large number of teachers and the fact that many of them are regular drivers, the sector presents an opportunity to design a formal carpooling transport system. This paper presents the design of a proposal for a carpooling system among workers from the education sector in the region of Andalusia, Spain. The system yielded relevant benefits such as cost savings, emissions reductions, and a high number of potential users. The designed system can potentially improve transport conditions for workers in commuting displacements and reduce occupational traffic accidents. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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26 pages, 6207 KiB

Open AccessArticle

Defining a Digital Strategy in a BIM Environment to Manage Existing Reinforced Concrete Bridges in the Context of Italian Regulation

by Angelo Ciccone, Pompilio Suglia, Domenico Asprone, Antonio Salzano and Maurizio Nicolella

Sustainability 2022, 14(18), 11767; https://doi.org/10.3390/su141811767 - 19 Sep 2022

Cited by 6 | Viewed by 2406

Abstract

Regulatory activity concerning the management of existing bridges has recently been affected by updates, for instance, in Italy, which calls for a speedy and pragmatic approach based on new technologies such as building information modeling (BIM), when dealing with the survey and risk classification as well as the evaluation and monitoring of structural safety. This paper focuses on the development and integration of a digital solution, based principally on the specific framework developed by the authors, which supports BIM modeling and information management activities, in the structural setting under investigation, through the use of several technologies and tools, namely BIM-authoring, CDE platform and visual programming, in addition to programming in Python. Starting from the organization of a specific BIM object library and the initial data, inserted by means of a custom-made input environment, it was possible to reproduce digital models of bridges in accordance with specific information requirements following the new Level of Information Need setting. The applicability of the proposal is tested on two judiciously chosen real-life cases with different characteristics. Through this implementation, a series of advantages emerge, including expediting traditional procedures for BIM modeling, accessibility and traceability of information—which are constantly updated to support the monitoring of structural safety over time—and the decision-making process related to the bridge management context. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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Review

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34 pages, 752 KiB

Open AccessReview

Natural Asphalts in Pavements: Review

by Hugo Alexander Rondón-Quintana, Juan Carlos Ruge-Cárdenas and Carlos Alfonso Zafra-Mejía

Sustainability 2023, 15(3), 2098; https://doi.org/10.3390/su15032098 - 22 Jan 2023

Cited by 8 | Viewed by 3272

Abstract

Natural asphalts (NAs) can be an economical and environmental alternative in pavement construction. Most studies have investigated them as binder and asphalt mixture modifiers due to their high compatibility with conventional asphalts. In this article, some of the studies carried out on the use of NA in pavements are summarized and described in a chronological order. The main aspects described in the reviewed studies were the type of asphalt binder or modified mixture, the type and content of the modifier, the manufacturing processes of the asphalt or modified mixture, tests performed, and main results or conclusions. In general terms, NAs show better performance as binder and asphalt mixture modifiers in high-temperature climates. Additionally, they tend to improve water and ageing resistance. As main limitations, it is reported that NAs tend to negatively affect the workability and performance of asphalt mixtures in low-temperature climates. Finally, recommendations for future study topics are provided at the end of this paper. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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Other

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18 pages, 3894 KiB

Open AccessSystematic Review

A Systematic Literature Review of the Predictive Maintenance from Transportation Systems Aspect

by Olcay Özge Ersöz, Ali Fırat İnal, Adnan Aktepe, Ahmet Kürşad Türker and Süleyman Ersöz

Sustainability 2022, 14(21), 14536; https://doi.org/10.3390/su142114536 - 4 Nov 2022

Cited by 12 | Viewed by 6204

Abstract

With the rapid progress of network technologies and sensors, monitoring the sensor data such as pressure, temperature, current, vibration and other electrical, mechanical and chemical variables has become much more significant. With the arrival of Big Data and artificial intelligence (AI), sophisticated solutions can be developed to prevent failures and predict the equipment’s remaining useful life (RUL). These techniques allow for taking maintenance actions with haste and precision. Accordingly, this study provides a systematic literature review (SLR) of the predictive maintenance (PdM) techniques in transportation systems. The main focus of this study is the literature covering PdM in the motor vehicles’ industry in the last 5 years. A total of 52 studies were included in the SLR and examined in detail within the scope of our research questions. We provided a summary on statistical, stochastic and AI approaches for PdM applications and their goals, methods, findings, challenges and opportunities. In addition, this study encourages future research by indicating the areas that have not yet been studied in the PdM literature. Full article

(This article belongs to the Special Issue Future Prospects in Sustainable Engineering Development for Transport Infrastructures and Systems)

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