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Sustainable Development of Intelligent Rail Transit
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Sustainable Development of Intelligent Rail Transit

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

Deadline for manuscript submissions: closed (16 October 2023) | Viewed by 3627

Special Issue Editors

Dr. Xin Zhang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Interests: prognostic and health management for rail transit
Dr. Zhiwen Liu

E-Mail Website
Guest Editor
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: intelligent operation and management for rail transit
Dr. Shuguang Li

E-Mail Website
Guest Editor
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: automatic driving; intelligent security guarantee
Dr. Yulin Jin

E-Mail Website
Guest Editor
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Interests: energy-saving technologies and applications

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue: Sustainable Development of Intelligent Rail Transit. Intelligent rail transit is a key component of sustainable transport policy, which aims to reduce greenhouse gas emissions, improve energy efficiency, enhance accessibility and mobility, and promote social equity and economic development. Intelligent rail transit refers to the application of advanced technologies, such as artificial intelligence, machine learning, robotics, automation, and digitalization, to improve the performance, safety, reliability, and convenience of rail systems. This research field is of great importance for addressing the challenges of urbanization, climate change, congestion, pollution, and public health that many regions face today. In this Special Issue, we will explore the latest developments and innovations in intelligent rail transit from various perspectives and discuss their implications for policy making and future research.

This Special Issue aims to showcase the latest research and innovation in the sustainable development of intelligent rail transit and inspire more scholars who are interested in the field and willing to get involved. We are interested in works related to theoretical, algorithmic, metric, and dataset advances, as well as new applications. This Special Issue will provide a timely collection of highly novel and original ideas for the broader community, e.g., intelligent operation and management, prognostic and health management, energy saving and emission reduction, and intelligent security guarantee.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

(1) Intelligent operation and management

  • Intelligent system for passenger flow monitoring and guidance
  • Intelligent safety supervision system
  • Intelligent station emergency response

(2) Prognostic and health management

  • Fault diagnosis of critical rail transit components
  • Remaining useful life prediction of critical rail transit components
  • Acquisition, storage, processing, and analysis of rail transit equipment status data

(3) Energy saving and emission reduction

  • New energy technology application
  • Energy-saving technologies (e.g., permanent magnet motors, vehicle lightweight, intelligent lighting, energy management)
  • Intelligent optimization for energy-saving operation of automatic train driving

(4) Intelligent security guarantee

  • Safety risk assessment of automatic driving system
  • Operation and maintenance management of the whole life cycle of rail transit facilities and equipment
  • Monitoring of the environment and obstacles on the rail transit operation

We look forward to receiving your contributions.

Dr. Xin Zhang
Dr. Zhiwen Liu
Dr. Shuguang Li
Dr. Yulin Jin
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. 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

  • intelligent rail transit
  • sustainable transport
  • artificial intelligence
  • intelligent operation and management
  • prognostic and health management
  • energy saving
  • emission reduction
  • intelligent security guarantee

Published Papers (2 papers)

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16 pages, 24782 KiB  
Article
Numerical Investigations of Tribological Characteristics of Biomimetic-Textured Surfaces
by Cheng Wang, Jianlin Cai, Gong Cheng, Jiaxu Wang and Dongxing Tang
Sustainability 2023, 15(17), 13054; https://doi.org/10.3390/su151713054 - 30 Aug 2023
Cited by 1 | Viewed by 839
Abstract
Rail transportation has dramatically improved travel convenience, but it has also led to environmental pollution and energy consumption issues. These challenges can be partially addressed by reducing friction loss in the mechanical transmission of rail systems. This paper examines the tribological properties of [...] Read more.
Rail transportation has dramatically improved travel convenience, but it has also led to environmental pollution and energy consumption issues. These challenges can be partially addressed by reducing friction loss in the mechanical transmission of rail systems. This paper examines the tribological properties of bionic-textured surfaces inspired by snake- and sharkskin. This study focuses on generating bionic textured surfaces with randomly distributed peaks through numerical simulation and connecting them to a transient Reynolds equation and friction fatigue model. The bionic surface wear lubrication model considers the lubricating film’s thickness and contact pressure obtained from the GT model. The results reveal that the existence of a bionic texture can reduce the friction coefficient and wear amount on the contact surface. The findings of this study not only offer a potential solution for reducing energy consumption and emissions in intelligent rail transit systems but also hold promise for providing further insights into the numerical simulation of bionic weaving and the investigation of tribological characteristics. Full article
(This article belongs to the Special Issue Sustainable Development of Intelligent Rail Transit)
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32 pages, 3458 KiB  
Systematic Review
The Development of Efficiency Analysis in Transportation Systems: A Bibliometric and Systematic Review
by Thiago Victorino and Carlos Rosano Peña
Sustainability 2023, 15(13), 10300; https://doi.org/10.3390/su151310300 - 29 Jun 2023
Cited by 1 | Viewed by 1705
Abstract
This paper presents a literature review of efficiency analysis in transportation systems (TS). It builds a bibliometric review of published data-envelopment analysis and, for the first time, stochastic frontier analysis publications in TS. The retrieved publications were separated into five groups: highway/road transportation, [...] Read more.
This paper presents a literature review of efficiency analysis in transportation systems (TS). It builds a bibliometric review of published data-envelopment analysis and, for the first time, stochastic frontier analysis publications in TS. The retrieved publications were separated into five groups: highway/road transportation, air transportation, maritime/port transportation, railway transportation, and urban/bus transportation. The 135 data-envelopment-analysis rail-related publications were surveyed to assess the model used, the second-stage analysis (if any), the input–output variables, the model orientation, return-to-scale assumptions, and their methodological classification. The results show that frontier methods in transportation systems have gained relevance since 2017. Also, gaps in the literature and future directions have been identified in empirical rail research, such as eco-efficiency and safety-related issues, as well as the need for a better investigation of variable choice and scale return assumptions. Finally, this paper proposes a step-by-step methodology for data envelopment analysis in rail systems. Full article
(This article belongs to the Special Issue Sustainable Development of Intelligent Rail Transit)
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