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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: 12 January 2025 | Viewed by 1109

Special Issue Editor


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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 (1 paper)

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Research

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
Viewed by 669
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
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