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Applied Sciences
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Application of Intelligent Transportation Systems in Railway: 2nd Edition
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Application of Intelligent Transportation Systems in Railway: 2nd Edition

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

Deadline for manuscript submissions: 30 July 2024 | Viewed by 2889

Special Issue Editors

Prof. Dr. Raimond Matthias Wüst

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Guest Editor
Institute for Data Analysis and Process Design, ZHAW School of Engineering, Technikumstrasse 9, 8400 Winterthur, Switzerland
Interests: service intention in railways; stability and robustness in rail operation; periodic timetables; maintenance plans in rail operation; simulation of rail systems
Special Issues, Collections and Topics in MDPI journals
Dr. Valerio De Martinis

E-Mail Website
Guest Editor
Institute for Data Analysis and Process Design, Zurich University of Applied Sciences (ZHAW), Winterthur, Switzerland
Interests: public transport design and operation; rail traffic management; train operation optimization; energy efficiency and public transport systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to a second Special Issue of Applied Sciences on the subject of “Application of Intelligent Transportation Systems in Railway”.

ITSs are defined as those systems that integrate different technologies in a synergetic way and follow systems engineering concepts to develop and improve transportation systems. In this field, the number of ITS solutions specifically developed for railway applications is increasing due to the incredible challenges that rail systems are facing to keep supporting the productivity of our society in a sustainable way. In this context, this Special Issue welcomes papers on current and future applications of ITSs in railway systems to make rail systems safer and smarter, to provide intelligent and friendly service to passengers and goods, and to optimize the operations and control of rail systems while guaranteeing high-standard efficiency.

We are seeking contributions addressing topics including (but not limited to):

  • Infrastructure (e.g., planning, construction, maintenance, power supply systems, communication systems, signaling systems);
  • Rail traffic management (e.g., capacity assessment, line planning, timetabling, traffic control, train operation, energy efficiency, crew scheduling);
  • Vehicle (e.g., ATO systems, light materials/new wagon concepts, onboard batteries, energy-saving speed profiles, virtual coupling);
  • Rail freight (e.g., planning, operation, new rail freight vehicle concepts, optimal vehicle composition and wagons disposition, urban rail freight);
  • Information from/to customers (e.g., smart card data, mobile apps, disruption management).

Other contributions pertaining the role of ITSs in railways are more than welcome.

The main aim of this Special Issue is to publish papers which present strategies to reduce the gap between practical demand and academic supply; therefore, papers based on the activities of research projects with academic/industrial partnerships are very welcome.

We look forward to receiving your contributions.

Prof. Dr. Raimond Matthias Wüst
Dr. Valerio De Martinis
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. 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.

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Published Papers (3 papers)

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Research

25 pages, 6608 KiB  
Article
Real-Time Adjustment Method for Metro Systems with Train Delays Based on Improved Q-Learning
by Yushen Hu, Wei Li and Qin Luo
Appl. Sci. 2024, 14(4), 1552; https://doi.org/10.3390/app14041552 - 15 Feb 2024
Cited by 1 | Viewed by 539
Abstract
This paper presents a solution to address the challenges of unexpected events in the operation of metro trains, which can lead to increased delays and safety risks. An improved Q-learning algorithm is proposed to reschedule train timetables via incorporating train detention and different [...] Read more.
This paper presents a solution to address the challenges of unexpected events in the operation of metro trains, which can lead to increased delays and safety risks. An improved Q-learning algorithm is proposed to reschedule train timetables via incorporating train detention and different section running times as actions. To enhance computational efficiency and convergence rate, a simulated annealing dynamic factor is introduced to improve action selection strategies. Additionally, importance sampling is employed to evaluate different policies effectively. A case study of Shenzhen Metro is conducted to demonstrate the effectiveness of the proposed method. The results show that the method achieves convergence, fast computation speed, and real-time adjustment capabilities. Compared to traditional methods such as no adjustment, manual adjustment, and FIFO (First-In-First-Out), the proposed method significantly reduces the average total train delay by 54% and leads to more uniform train headways. The proposed method utilizes a limited number of variables for practical state descriptions, making it well suited for real-world applications. It also exhibits good scalability and transferability to other metro systems. Full article
(This article belongs to the Special Issue Application of Intelligent Transportation Systems in Railway: 2nd Edition)
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17 pages, 1013 KiB  
Article
Robust Optimization of Transport Organization for China Railway Express
by Changjiang Zheng, Yang Shen, Junze Ma, Ling Gui and Chen Zhang
Appl. Sci. 2024, 14(1), 137; https://doi.org/10.3390/app14010137 - 22 Dec 2023
Viewed by 685
Abstract
This paper presents an in-depth analysis of the robust optimization of the China–Europe freight train transportation organization under uncertain cargo transportation demand. The study commences by constructing a robust optimization model tailored for specific environments, which is further extended to address the complexities [...] Read more.
This paper presents an in-depth analysis of the robust optimization of the China–Europe freight train transportation organization under uncertain cargo transportation demand. The study commences by constructing a robust optimization model tailored for specific environments, which is further extended to address the complexities of uncertain freight demand. A notable aspect of this research is the adoption of an innovative approach to manage the uncertainties in freight transportation demand at each node, employing a box-type uncertainty set distribution. This methodology allows for an effective and balanced optimization strategy that accommodates the dynamic nature of demand fluctuations. The research findings underscore that increased robustness in the optimization model is associated with higher transportation costs within the China–Europe freight train network, especially under conditions of variable demand. The model demonstrates a preference for adjusting transportation costs to maintain the stability of the transportation scheme, particularly in response to wider variations in cargo demand. This strategy, prioritizing cost-effectiveness and adaptability, highlights the importance of a comprehensive approach to managing demand uncertainties. The significant contributions of this paper include the development of a robust, economically viable, and efficient transportation organization plan for China–Europe freight trains, equipped to navigate the challenges posed by uncertain cargo demand at the originating nodes. The study’s emphasis on the practical application of advanced optimization techniques and uncertainty management methods marks a notable advancement in the field of freight train transportation. Additionally, the paper suggests avenues for further research in the intricate and evolving landscape of freight transportation, providing valuable insights for future studies. Full article
(This article belongs to the Special Issue Application of Intelligent Transportation Systems in Railway: 2nd Edition)
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21 pages, 2786 KiB  
Article
Optimization of High-Speed Rail Express Transportation Plan Considering Products’ Variable Time Requirements
by Teer Lu, Junhua Chen, Chunxiao Zhao and Xiaoling Xie
Appl. Sci. 2023, 13(12), 6919; https://doi.org/10.3390/app13126919 - 7 Jun 2023
Viewed by 1212
Abstract
The global express market has expanded significantly in recent years. High-speed rail express freight transportation has been implemented between multiple cities in China, significantly improving transportation efficiency and effectively meeting demand. In this paper, an optimization model for HSR (high-speed railway) express transport [...] Read more.
The global express market has expanded significantly in recent years. High-speed rail express freight transportation has been implemented between multiple cities in China, significantly improving transportation efficiency and effectively meeting demand. In this paper, an optimization model for HSR (high-speed railway) express transport plan is constructed using a space-time-state network, and an improved adaptive genetic algorithm is designed to solve the model. Reasonable transport schemes could be arranged for each cargo flow with the objective of maximizing operational revenue. The numerical experiment based on the Harbin–Dalian high-speed railway in China verifies the effectiveness and applicability of the proposed model. The results show that for HSR operators, appropriate transport strategies can be planned in terms of delivery priorities and transportation mode selection to make full use of the remaining capacity of HSR trains and increase operational revenue. Full article
(This article belongs to the Special Issue Application of Intelligent Transportation Systems in Railway: 2nd Edition)
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