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Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization

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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 September 2026 | Viewed by 3724

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Special Issue Editors

Prof. Dr. Heinrich D. Foltz

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Guest Editor

Department of Electrical and Computer Engineering, College of Engineering and Computer Science, The University of Texas Rio Grande Valley, Edinburg, TX 78539, USA
Interests: railway systems; antennas and wireless communications

Dr. Brent Wilson

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Guest Editor

HUM Industrial Technology, Inc., San Diego, CA, USA
Interests: railroad bearing failure analysis and mitigation; railroad

Special Issue Information

Dear Colleagues,

Railways are increasingly making use of advanced technologies in the forms of integrated sensors, remote automation, and artificial intelligence to enhance quality of service, reduce cost of operation, and most importantly, reduce the chance of collisions, derailments, and other accidents. This Special Issue aims to explore the advancements, challenges, and applications of sensors and automation in modern rail systems. Papers are invited on that consider sensor hardware and design, modeling, algorithms, and system integration, with focuses including, but not limited to, the following topics:

Railcar condition monitoring, both onboard and wayside;
Track and ballast condition monitoring;
Automatic identification of hazards in the right-of-way and grade crossings;
Advances in positive train control, including moving block control;
Autonomous train systems;
Railway safety policy;
Advanced vision systems for safety and/or tracks;
Railcar dynamics;
In-train forces;
Damage prevention.

We look forward to receiving your contributions.

Prof. Dr. Heinrich D. Foltz
Dr. Brent Wilson
Guest Editors

Manuscript Submission Information

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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.

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Keywords

railway system
vibration analysis
railroad bearing performance
realistic routes
railway safety
onboard monitoring systems
condition monitoring
predictive maintenance
fault detection
structural health monitoring
sensor networks
internet of things (IoT)
smart scheduling
intelligent control
autonomous train operation (ATO)
communication-based train control (CBTC)
traffic management
energy efficiency
resilience

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Published Papers (5 papers)

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Research

21 pages, 3703 KB

Open AccessArticle

Optimization and Solution of Shunting Plan Formulation Model for EMU Depot Considering Maintenance Capacity

by Hua Zhang, Qichang Li, Bingyue Lin, Yanyi Liu and Xinpeng Zhang

Appl. Sci. 2026, 16(1), 477; https://doi.org/10.3390/app16010477 - 2 Jan 2026

Viewed by 443

Abstract

In this paper, we take the longitudinal two-stage and two-yard EMU (Electric Multiple Unit) depot as an example and discusses the optimization challenges of the first-level maintenance shunting operation plan under the background of limited maintenance capacity. A multi-objective programming is constructed, which adopts the lexicographic ordering method and aims to minimize the occupancy time of key line areas and the number of train storage times. In order to enhance the flexibility and solution efficiency of the shunting operation plan, we design an efficient three-stage strategy algorithm. Specifically, in the first stage, the genetic and mutation rules are integrated, and the fast iterative advantage of the genetic algorithm is utilized to solve the time decision variables in the optimization problem. In the second stage, the allocation of track occupancy variables is further solved. The third stage focuses on the optimized allocation of maintenance team variables to ensure the scientific scheduling of maintenance resources. Finally, a validation experiment was conducted using the maintenance tasks of 19 EMU sets as the test scenario. The results indicate that when the number of maintenance teams is set to 4, an optimal balance between maintenance efficiency and operational cost is achieved, the occupancy duration of key line zones reaches 3034 min (the theoretical optimum), the number of maintenance teams is reduced by 33.33% compared to the initial 6 teams, and the number of storage operations is optimized to 27 times. Additionally, the algorithm’s solution time remains under 50 s, demonstrating significantly improved computational efficiency. Comparative experiments with baseline algorithms show that the proposed method reduces the occupancy duration of key line zones by up to 0.49%, decreases the number of storage operations by 14 times, and advances the maximum completion time by 20 min. In summary, the proposed method provides solid theoretical support for the formulation of maintenance plans and shunting schedules in EMU depots. Particularly in complex scenarios with limited maintenance capacity, it offers innovative and robust decision-making foundations, demonstrating significant practical guidance value. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

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29 pages, 1796 KB

Open AccessArticle

Enhancing Fairness in High-Speed Railway Crew Scheduling: A Two-Stage Heuristic Optimization Framework Under Daily-Adjusted Timetables

by Chen Wan, Tianyi Sheng, Hua Li, Yuliang Zhang and Chengcheng Yu

Appl. Sci. 2026, 16(1), 376; https://doi.org/10.3390/app16010376 - 29 Dec 2025

Cited by 1 | Viewed by 520

Abstract

The existing crew base assignment system in high-speed railway operations struggles to cope with the frequent deployment of additional and coupled trains under the “One-Day-One-Operation Plan” dynamic scheduling paradigm. This often results in unequal overtime distribution among crews, low scheduling efficiency, and limited operational adaptability. To address the above-mentioned application challenges, this study proposes a shift from the fixed crew-based system towards a fully flexible pool-based system. Specifically, we develop a novel integer programming model designed to optimize monthly crew schedules with the primary objective of balancing total working hours across all crew teams. In this model, crew teams are treated as unified entities but are no longer permanently tied to specific train services. Instead, they are dynamically allocated to all available train tasks within the network. Numerical results, based on a real-world case study from Shanghai, China, demonstrate that the proposed model effectively automates the scheduling process. It significantly enhances fairness in working hour distribution while fully complying with all operational rules. Furthermore, by enabling crews to undertake a diverse range of services, the model substantially improves the flexibility of human resource allocation and the overall robustness of the crew management system. This research provides an efficient and scientific decision-support tool for tackling crew scheduling difficulties in dynamic railway operations. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

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20 pages, 3824 KB

Open AccessArticle

The Problem of Resolving Train Movement Conflicts in a Traffic Management System

by Janusz Szkopiński, Maciej Śmieszek and Andrzej Kochan

Appl. Sci. 2025, 15(23), 12770; https://doi.org/10.3390/app152312770 - 2 Dec 2025

Cited by 1 | Viewed by 839

Abstract

This article addresses selected aspects of designing a Traffic Management System (TMS) for the railway component of Poland’s Central Communication Port (CPK) project. The primary objective was to determine train headway times while considering automated traffic conflict resolution and speed profile optimization in relation to traction energy consumption. The study utilized simulations in the MATLAB/Simulink (Version number: R2024a Update 3) environment, modeling the movement of an ETR610 (ED250) train on a line equipped with the European Train Control System (ETCS). The simulation results provided insights into the impact of the adopted assumptions on TMS operational efficiency under failure conditions and its capability to optimize train movements. The conclusions underscore the critical importance of time reserves in effective conflict resolution, the interplay between buffer allocation and speed restrictions, and the impact of minimizing train stops on energy consumption. They also highlight the necessity of adapting operational strategies to infrastructure characteristics and the influence of simulation time on the effectiveness of conflict resolution methods. Furthermore, the study emphasizes the need to broaden operational scenarios to include failures of traction vehicles and train control systems, along with appropriate planning for time reserves. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

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16 pages, 3365 KB

Open AccessArticle

Study on Breakdown Characteristics of On-Train High-Voltage Combined Electrical Apparatus Under Lightning Transient Conditions

by Jixing Sun, Kun Zhang, Yide Liu, Sile Yang and Jiuding Tan

Appl. Sci. 2025, 15(22), 12238; https://doi.org/10.3390/app152212238 - 18 Nov 2025

Viewed by 596

Abstract

The high-voltage system of high-speed trains is now in the form of combined electrical apparatus, which has a high probability of insulation breakdown due to frequent overvoltage during operation. To solve this issue, an electric field simulation model of the high-voltage combined electrical system was established, the electric field distribution of the high-voltage box electrode under overvoltage operating conditions was analyzed, and the air breakdown characteristics under field action were studied. The study shows that under overvoltage conditions, the electric field intensity near the small electrodes of the combined electrical unit is higher than the air breakdown field intensity, and the statistical time delay is approximately 5.94 μs when 150 kV voltage is applied. When the size of the connected electrode is doubled and 150 kV voltage is applied, the statistical delay is about 7.20 μs and the probability of discharge is reduced. Further installation of an insulating partition between the circuit breaker and the ground switch completely solved the problem of low electrical gap insulation capacity. Combined with impulse withstand tests, the effectiveness of the electrode size design was verified, and the research results provided theoretical support for the miniaturization and high-reliability design of vehicle-mounted high-voltage electrical appliances. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

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21 pages, 4100 KB

Open AccessArticle

Data-Driven Condition Monitoring of Fixed-Turnout Frogs Using Standard Track Recording Car Measurements

by Markus Loidolt, Julia Egger and Andrea Katharina Korenjak

Appl. Sci. 2025, 15(20), 11122; https://doi.org/10.3390/app152011122 - 16 Oct 2025

Cited by 2 | Viewed by 818

Abstract

Turnouts are critical components of railway infrastructure, ensuring operational flexibility but also representing a significant share of track maintenance costs. The frog, as the most vulnerable part of a turnout, is subject to severe wear and degradation, requiring frequent inspection and maintenance. Traditional manual inspection methods are costly, labour-intensive, and susceptible to subjectivity. This study explores a data-driven approach to condition monitoring of fixed-turnout frogs using standard track recording car measurements. By leveraging over 20 years of longitudinal level and rail surface signal data from the Austrian track-recording measurement car, we assess the feasibility of using existing measurement data for predictive maintenance. Six complementary approaches are proposed to evaluate frog condition, including track geometry assessment, ballast condition analysis, rail surface irregularity detection, and axle box acceleration-based monitoring. Results indicate that data-driven monitoring enhances maintenance decision-making by identifying deterioration trends, reducing reliance on manual inspections, and enabling predictive interventions. The integration of standardised measurement data with advanced analytical models offers a cost-effective and scalable solution for turnout maintenance. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

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