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Intelligent Management and Application of Sustainable Transportation Systems
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Intelligent Management and Application of Sustainable Transportation Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (12 January 2025) | Viewed by 3722

Special Issue Editor

Dr. Guoqiang Cai

E-Mail Website
Guest Editor
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Interests: non-destructive testing; damage detection and structural health monitoring; computational modeling and simulation; multi-scale analysis; environmental effects on composite materials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The AI wave is sweeping the world. The milestone for carbon neutrality agreed upon in the Paris Agreement is imminent. Sustainable transportation systems are crucial to both economic and urban development, and an intensive, efficient, economic, intelligent, green, safe, and reliable transportation system is key with regard to a country's economic growth, carbon footprint reduction, and its citizens' living standards. To firmly grasp this important opportunity, it is necessary to combine emerging technologies with traditional transportation systems, solve major scientific challenges, and enable sustainable transportation systems with intelligent management and applications embedded within.

The focus of this Special Issue is to investigate how transportation processes can be made efficient, intelligent, green, and safe. Our goal is to facilitate further discussions regarding sustainable urban transportation, intelligent transportation systems, and other relevant topics within the exciting field of sustainable transportation. A variety of solutions and technologies will be investigated, with innovative and smart technologies being integrated into transportation projects. In addition, we will examine the use of eco-friendly energy sources, the implementation and application of safety measures, and the reduction in traffic congestion and carbon emissions while simultaneously increasing economic benefits. This Special Issue welcomes original research articles and comments. Research areas may include (but are not limited to) the following:

  • Intelligent transportation systems;
  • Collaborative management and transportation efficiency;
  • Structural health monitoring and maintenance;
  • Traffic safety detection technology;
  • Transportation big data analysis and artificial intelligence;
  • Environmental protection technology related to transportation;
  • Simulation environment and new modeling tools;
  • Advanced safety devices and support systems.

Dr. Guoqiang Cai
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. Applied Sciences 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

  • intelligent transportation systems
  • transportation safety inspection technology
  • transportation simulation
  • environmental protection

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Published Papers (4 papers)

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Research

31 pages, 1306 KiB  
Article
Evaluation of Adjustment Effects of Highway Guide Signs Based on the TOPSIS Method
by Jin Ran, Meiling Li, Jian Rong, Ding Zhao, Ahmetjan Kadir and Qiang Luo
Appl. Sci. 2025, 15(9), 4949; https://doi.org/10.3390/app15094949 (registering DOI) - 29 Apr 2025
Abstract
With the rapid expansion of highway networks, the demand for timely and reliable road information has steadily increased. However, some guide signs on newly built or extended highways in China have not been updated or adjusted in time, resulting in incomplete information and [...] Read more.
With the rapid expansion of highway networks, the demand for timely and reliable road information has steadily increased. However, some guide signs on newly built or extended highways in China have not been updated or adjusted in time, resulting in incomplete information and non-standard setups. These issues not only affect drivers’ navigation experience but may also negatively impact road safety and traffic efficiency. Therefore, it is crucial to establish a scientifically sound evaluation system and a comprehensive assessment model for highway guide signs. This study selected a representative highway (G2 Expressway in China) as the research subject and combined questionnaire surveys with field investigations to identify common issues such as vague information and irregular placement of guide signs. Through an in-depth analysis of travel demand, the core requirements of drivers were summarized as safety, efficiency, and comfort. Based on these insights, the study proposes four key design principles for guide signs: standardization, readability, continuity, and consistency. A set of quantifiable evaluation indicators was developed through a comprehensive analysis of key factors affecting signage performance, and factor analysis was applied to verify the independence and rationality of the indicators. On this basis, an evaluation model was constructed using the technique for order preference by similarity to ideal solution (TOPSIS) to scientifically quantify the effectiveness of guide signs. The model was applied in a field study on the Hebei section of the G2 Expressway in China (with comprehensive traffic sign coverage, high traffic volume, and more traffic sign issues), with results demonstrating the feasibility and practicality of the proposed evaluation system and model. This research offers a systematic solution to enhance the service quality of highway guide signs and provides essential references for future highway planning and management practices. It aims to comprehensively improve drivers’ travel experiences and promote the development of sustainable and intelligent transportation networks, offering valuable insights for building integrated urban systems. Full article
(This article belongs to the Special Issue Intelligent Management and Application of Sustainable Transportation Systems)
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29 pages, 6896 KiB  
Article
Research on Modeling and Analysis Methods of Railway Station Yard Diagrams Based on Multi-Layer Complex Networks
by Pengfei Gao, Wei Zheng, Jintao Liu and Daohua Wu
Appl. Sci. 2025, 15(5), 2324; https://doi.org/10.3390/app15052324 - 21 Feb 2025
Cited by 2 | Viewed by 550
Abstract
Optimizing railway station operations necessitates the identification of critical track sections that constrain design throughput capacity under fixed infrastructure conditions. This paper proposes a novel multi-layer complex network-based approach for modeling and analyzing railway station yard diagrams, reframing the identification of key track [...] Read more.
Optimizing railway station operations necessitates the identification of critical track sections that constrain design throughput capacity under fixed infrastructure conditions. This paper proposes a novel multi-layer complex network-based approach for modeling and analyzing railway station yard diagrams, reframing the identification of key track sections affecting station throughput capacity as a node importance evaluation problem. In this model, nodes represent track sections included in routes specified by the station interlocking tables, while edges denote sequential connections between nodes. The structural relationships among nodes are captured using adjacency matrix (AM), structural matrix (SM), connection count matrix (CCM), and transition probability matrix (TPM). To evaluate node importance, five key indicators are introduced: connectivity strength (CS), destination node count (DNC), source node count (SNC), node efficiency (NE), and an extended PageRank (EPR). Additionally, a layered network node importance analysis method based on a single indicator, along with a comprehensive evaluation approach for the importance of the multi-layer network node, is presented. A case study conducted on a conventional railway station demonstrates that the proposed method effectively identifies key track sections through both hierarchical single-indicator evaluation and comprehensive assessment approaches. Furthermore, this paper investigates key node evaluation indicators and explores an alternative method based on Principal Component Analysis and Rank Sum Ratio (PCA-RSR), which also proves effective in identifying critical track sections. Full article
(This article belongs to the Special Issue Intelligent Management and Application of Sustainable Transportation Systems)
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14 pages, 4499 KiB  
Article
Rural Road Assessment Method for Sustainable Territorial Development
by Leonardo Sierra-Varela, Álvaro Filun-Santana, Felipe Araya, Noé Villegas-Flores and Aner Martinez-Soto
Appl. Sci. 2024, 14(23), 11021; https://doi.org/10.3390/app142311021 - 27 Nov 2024
Cited by 1 | Viewed by 1105
Abstract
In Latin America, initiatives have been advocated for developing rural roads that facilitate optimal conditions free from dust, mud, and noise. The criteria for assessing public investment do not align with the requirements of rural infrastructure. Indeed, in rural areas, the territorial conditions [...] Read more.
In Latin America, initiatives have been advocated for developing rural roads that facilitate optimal conditions free from dust, mud, and noise. The criteria for assessing public investment do not align with the requirements of rural infrastructure. Indeed, in rural areas, the territorial conditions such as openness to rural–urban markets, access to education and health, environmental protection, culture, and identity are more important than transportation times or traffic volume. Hence, a multicriteria evaluation method is proposed to prioritize the rural road improvements and maximize their contribution to sustainable territorial development. The roads with the highest sustainable contribution are optimized using a multi-objective decision-making analysis and prioritized based on a Manhattan distance. In addition, a fuzzy cognitive map analyzes the dynamic behavior of the optimal roads. Based on this proposal, a case study is applied where fifteen roads are selected from a sample of 101 in the Araucanía Region, Chile. For this, 16 evaluation criteria, 27 indicators, and sustainability’s social, environmental, technical, and economic dimensions are considered. The results detect reduced one-dimensional contributions despite identifying 15 optimal roads that collectively enhance sustainability. Two roads stand out for their long-term sustainability contribution, which are influenced by economic criteria of zonal productivity, tourism, and road maintenance. Thus, this method can help public agencies rank the roads that must be the subject of development projects. Full article
(This article belongs to the Special Issue Intelligent Management and Application of Sustainable Transportation Systems)
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15 pages, 2914 KiB  
Article
An Improved Target Network Model for Rail Surface Defect Detection
by Ye Zhang, Tianshi Feng, Yating Song, Yuhang Shi and Guoqiang Cai
Appl. Sci. 2024, 14(15), 6467; https://doi.org/10.3390/app14156467 - 24 Jul 2024
Cited by 1 | Viewed by 1428
Abstract
Rail surface defects typically serve as early indicators of railway malfunctions, which may compromise the quality and corrosion resistance of rails, thereby endangering the safe operation of trains. The timely detection of defects is essential to ensure the safe operation of railways. To [...] Read more.
Rail surface defects typically serve as early indicators of railway malfunctions, which may compromise the quality and corrosion resistance of rails, thereby endangering the safe operation of trains. The timely detection of defects is essential to ensure the safe operation of railways. To improve the classification accuracy of rail surface defect detection, this paper proposes a rail surface defects detection algorithm based on MobileNet-YOLOv7. By integrating lightweight deep learning algorithms into the engineering application of rail surface defect detection, a MobileNetV3 lightweight network is used as the backbone network for YOLOv7 to enhance both speed and accuracy in complex defect extraction. Subsequently, the efficient intersection over union (EIOU) loss function is utilized as the positional loss function to bolster system resilience. Finally, the k-means++ clustering algorithm is applied to obtain new anchor boxes. The experimental results demonstrate the effectiveness of the proposed method, achieving superior detection accuracy compared with traditional algorithms. Full article
(This article belongs to the Special Issue Intelligent Management and Application of Sustainable Transportation Systems)
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