Smart Railway Research Articles

A time-space network-based model for transportation service optimization of China Railway Express

This paper describes the development and optimization plans for the China Railway Express (CR Express). As a new type of international land transport organization, CR Express has emerged with the continuous expansion of China toward European investment and trade, and in particular, has expanded with the continuous progress of the One Belt and One Road (OBOR) initiative. In addition to improving the service quality of CR Express, the operating costs must be reduced for developing “smart railways” that serve “smart cities”. We propose a dual-objective-based function mathematical optimization model; the satisfaction of the cargo owner is considered, and the timeliness, transportation capacity, and goods category constraints of CR Express transportation are designed. Moreover, we present the normalized equivalent method of the two-objective function of the model. Finally, a case study is conducted against the background of certain trains in the western corridor of CR Express to validate the effectiveness of the model and research methods proposed in this study.

Smart Railway Gate Level Crossing System

Smart Railway Gate Level Crossing System

A Novel Security Risk Analysis Using the AHP Method in Smart Railway Systems

Transportation has an essential place in societies and importance to people in terms of its social and economic aspects. Innovative rail systems need to be integrated with developing technologies for transportation. Systemic failures, personnel errors, sabotage, and cyber-attacks in the techniques used will cause a damaged corporate reputation and revenue losses. In this study, cybersecurity attack methods in smart rail systems were determined, and cyber events occurring worldwide through these technologies were analyzed. Risk analysis in terms of transportation safety in smart rail systems was determined by considering the opinions of 10 different experts along with the Analytic Hierarchical Process (AHP) performance criteria. Informatics experts were selected from a group of people with at least 5–15 years of experience. According to these risk analysis calculations, cybersecurity stood out as the most critical security risk at 27.74%. Other risky areas included physical security, calculated at 14.59%, operator errors at 16.20%, and environmental security at 10.93%.

Smart railways: the design and construction of an autonomous inspection and maintenance vehicle

The Railway Inspection and Maintenance Vehicle (RIMV) is a state-of-the-art autonomous ground robot for the railway environment. The robot has specialised hardware tailored for specific functionalities, ensuring optimal performance in its designated tasks. It incorporates a GPS, IMU, and encoder for robust localisation, and it integrates a LiDAR system and a depth camera for collision avoidance. Prioritising safety, the RIMV features an IP camera for real-time environmental monitoring and is equipped with emergency stop mechanisms. An Ubuntu Linux machine manages the robot’s data processing, complemented by a 5G Wi-Fi router for remote monitoring and operation when necessary. ROS2 is the primary platform for robot operations, standing out for its open-source solution and enhanced cybersecurity features. We validated the RIMV in a heritage railway setting with an ultrasonic inspection kit to detect rail-track defects. Beyond this specific application, the RIMV is versatile and designed to serve as a platform for other autonomous inspection and maintenance tasks within the railway sector. Its adaptability highlights its potential to enhance efficiency and safety in railway maintenance, offering invaluable assistance to human operators across varied scenarios.

Analysis of research on smart rail circuits

The purpose of the article is to study intelligent continuous-type rail circuits with current receivers, respectively, to identify the possibility of determining the unit located on the rail lines with a standard shunt prescribed in the operating rules, as well as monitoring for breakage of a continuoustype rail circuit. To study smart railway circuits, it is necessary to take into account the circuit diagram of this track circuit and its operation with various factors influencing it. One of the points of the study is to determine the maximum and minimum resistance at the beginning and at the end of this rail line and also taking into account the worst influencing parameters on an intelligent rail circuit of unlimited length, carry out calculations and determine on the graphs the probability of failure-free operation in all modes. The study took into account fluctuations in temperature decline, both during the seasons, winter, summer, etc., and sharp continental changes within an hour in operating mode. When conducting the study, we also took into account the insulating resistance that affects the power supply of the composition determination sensor, which leads to a dependence on the length of the smart sensor. The parameters of changes in the sensor supply voltage, its variability from the supplier and the resistance of the rails and their fluctuations were taken. For this purpose, the requirements for the length of the intelligent rail circuit, shunt resistance and insulation resistance used on the road were applied, as well as determining the influence of all unfavorable conditions.

Power management via STL specifications of a DC microgrid integrating renewables and storage devices: a smart railway station case study

This paper presents a method for defining and managing complex power management behaviors in microgrids that incorporate renewable energy sources, storage devices with different characteristics, and a connection to the main grid. In particular, we focus on a smart railway station that integrates regenerative braking energy from trains. The challenge lies in coordinating diverse microgrid components while adhering to constraints across multiple control levels. We use signal temporal logic (STL) to precisely define these complex objectives and integrate them into a model predictive control (MPC) framework. We present numerical simulations using a mixed-integer strategy to demonstrate the approach’s effectiveness.

Double-layer optimal energy management of smart grid incorporating P2P energy trading with smart traction system

Abstract Moving towards clean and sustainable transportation system, electrification of railway systems along with the use of electric vehicles (EVs) are of great interest. For economic operation of such systems, the peer-to-peer (P2P) energy trading policy became more applicable. Therefore, this paper proposes a double-layer individual-based optimization algorithm for P2P based optimal energy management (EM) of a smart distribution network incorporating flexible smart railway substation taking into consideration multiple energy sources of the traction system and the wayside distribution network with the integration of both EVs and energy hubs (EHs). For efficient operation of the railway substation, captured regenerative braking energy (RBE) are considered. In addition, photovoltaic (PV) units are used on station’s and platforms’ roof-tops for clean energy generation along with a multistory parking garage of electric vehicles (EVs). The wayside distribution network of district distribution area with flexible loads also contains several energy sources including distributed generation and multiple EHs. Optimal energy management is carried out including optimal demand side management of flexible loads and EHs. The optimization study takes into consideration several operational uncertainties arising from several components of the system. The simulation results show the feasibility of applying the proposed EM algorithm with an improvement of the energy economics of the system. The results show a reduction of 6.5 % in energy cost of the distribution network loads, 48 % in net energy cost of EHs, 70.8 % in net energy cost of EVs, and 59.1 % in the cost of energy bought by the traction substation.

Energy Management Systems for Smart Electric Railway Networks: A Methodological Review

Energy shortage is one of the major concerns in today’s world. As a consumer of electrical energy, the electric railway system (ERS), due to trains, stations, and commercial users, intakes an enormous amount of electricity. Increasing greenhouse gases (GHG) and CO2 emissions, in addition, have drawn the regard of world leaders as among the most dangerous threats at present; based on research in this field, the transportation sector contributes significantly to this pollution. Railway Energy Management Systems (REMS) are a modern green solution that not only tackle these problems but also, by implementing REMS, electricity can be sold to the grid market. Researchers have been trying to reduce the daily operational costs of smart railway stations, mitigating power quality issues, considering the traction uncertainties and stochastic behavior of Renewable Energy Resources (RERs) and Energy Storage Systems (ESSs), which has a significant impact on total operational cost. In this context, the first main objective of this article is to take a comprehensive review of the literature on REMS and examine closely all the works that have been carried out in this area, and also the REMS architecture and configurations are clarified as well. The secondary objective of this article is to analyze both traditional and modern methods utilized in REMS and conduct a thorough comparison of them. In order to provide a comprehensive analysis in this field, over 120 publications have been compiled, listed, and categorized. The study highlights the potential of leveraging RERs for cost reduction and sustainability. Evaluating factors including speed, simplicity, efficiency, accuracy, and ability to handle stochastic behavior and constraints, the strengths and limitations of each optimization method are elucidated.

Railway ballast track hanging sleeper defect detection using a smart CNT self-sensing concrete railway sleeper

Health monitoring of railway tracks has become an increasingly valuable aspect of railway track maintenance and is taking on a leading role. Considering the current limitations in monitoring of railway components such as ballast and sleepers, a new method of self-sensing smart railway sleeper has been proposed in this research. Carbon nanotubes (CNT) as a functional filler can provide intrinsic self-sensing properties to railway sleepers to detect hanging sleeper defects. Therefore, to analysis the effectiveness of the proposed idea to detect hanging sleeper defect the self-sensing behavior of CNT-cement composite specimens and real scale railway sleepers are studied with three different percentages of CNT as 0.5%, 0.75%, and 1% by cement weight under different support conditions of disturbed and full ballast supports, and different electrode distances. Experimental results show that CNT generates sensitivity for the specimens corresponding to applied loads. This sensitivity is the highest for 0.75 %CNT and 0.5 %CNT and inner electrode distances by 0.043 and 0.036 10-6.N−1. Considering the mechanical performance and sensitivity coefficient (kx), 0.5 %CNT and inner electrodes are the optimal combination of electrode distance and CNT content. FE modeling study shows that hanging defect highly enlarges the dynamic response of hanged sleepers than full support railway sleepers. This increase in dynamic loads due to hanging defect results in hanged sleeper detection using distinguishable sensitivity coefficient values. The kx response in 150 kN axle load is highly relied on train speed as the difference percentage of kx increases by 7% for speed of 100 km/h to 300 km/h.

Optimal P2P based energy trading of flexible smart inter-city electric traction system and a wayside network: A case study in Alexandria, Egypt

In an open energy market, the peer-to-peer (P2P) energy trading policy became more applicable. Therefore, while planning for new electrified systems, such a trading policy is taken into consideration. On the other hand, as the electrification of railway systems along with the use of electric vehicles serve several sustainable development goals, plans are studied for the electrification of the inter-city railway system in Alexandria, Egypt, in order to connect it with the high-speed inter-provincial electric railway system. In addition, other plans are studied for local production of electric vehicles. For this purpose, this paper presents a study regarding P2P based optimal energy management (EM) of a flexible smart railway substation taking into consideration multiple energy sources of the traction system and the wayside distribution network. The energy sources of the substation include captured regenerative braking energy (RBE), photovoltaic (PV) units and a multistory parking garage of electric vehicles (EVs). The wayside distribution network also contains several energy sources including distributed generation and multiple energy hubs (EHs) in addition to district distribution area with flexible loads. Optimal energy management is carried out including optimal demand side management of flexible loads and EHs. The optimization study takes into consideration several operational uncertainties arising from several components of the system. The simulation results show the feasibility of applying the proposed EM algorithm with an improvement of the energy economics of the system.

Energy management optimization in smart railway stations with the ability to charge plug-in hybrid electric vehicles

The increasing development of traffic in the world has led to an increase in the consumption of electrical energy in electric vehicles (EVs). One of the most widely used electric vehicles is the electric train. Thus, energy optimization becomes more crucial in electrical railways to reduce consumption and total electricity bill as well as environmental issues. Consequently, electrical railway energy management must be technically and economically efficient and effective. This paper proposes an energy efficiency optimization framework for intelligent railway stations that provide plug-in electric vehicle charging parking capacity use, renewable energy sources (REs), and regenerative braking energy (RBE). The structure of the proposed convex programming (CP) model is used for fast and efficient optimization of decision variables, Equipment size, and the cost function of the station for reducing the power purchased from the Grid. Furthermore, by presenting meta-heuristic algorithms, the state variables of the energy storage system (ESS) and Plug-in hybrid electric vehicles (PHEVs) battery have been optimized. The results obtained from the proposed method prove that the operation cost of the station decreases by 61.4 %.

Towards AI-assisted digital twins for smart railways: preliminary guideline and reference architecture

In the last years, there has been a growing interest in the emerging concept of digital twins (DTs) among software engineers and researchers. DTs not only represent a promising paradigm to improve product quality and optimize production processes, but they also may help enhance the predictability and resilience of cyber-physical systems operating in critical contexts. In this work, we investigate the adoption of DTs in the railway sector, focusing in particular on the role of artificial intelligence (AI) technologies as key enablers for building added-value services and applications related to smart decision-making. In this paper, in particular, we address predictive maintenance which represents one of the most promising services benefiting from the combination of DT and AI. To cope with the lack of mature DT development methodologies and standardized frameworks, we detail a workflow for DT design and development specifically tailored to a predictive maintenance scenario and propose a high-level architecture for AI-enabled DTs supporting such workflow.

Enabling OTFS-TSMA for Smart Railways mMTC Over LEO Satellite: A Differential Doppler Shift Perspective

Recently, grant-free orthogonal time–frequency space-based tandem spreading multiple access (OTFS-TSMA) is proposed for machine-type communications (mMTCs) in smart railways environmental sensing. To achieve massive connections with scarce radio resources, OTFS-TSMA combines the advantages of OTFS and TSMA. It shows high connectivity and reliability under time–frequency-selective fading channels. Meanwhile, smart railways require over-horizon and all-weather environmental sensing based on mMTC, and the implementation of both would cost a lot in terrestrial networks. With the development of low-Earth orbit (LEO) satellites, enabling smart railways mMTC over LEO satellite is a potential diagram. However, in this scenario, due to the larger transmission delay and Doppler frequency shift, the time–frequency resource requirements of the OTFS modulation-based system increase significantly and are difficult to meet. To this end, OTFS-TSMA based on differential Doppler shift is proposed in this article. Specifically, in this article, the satellite-to-ground communication system model consisting of three sections is introduced, and the Doppler shift and differential Doppler shift characteristics of access points (APs) are investigated. Next, it is proven that designing OTFS-based multiple access schemes over the LEO satellite based on differential Doppler shift is not only resource-friendly but also has the advantages of service continuity and controllable multiuser interference. Then, the transceiver of differential-Doppler-shift-based OTFS-TSMA and its improved designs are proposed. Finally, the simulation results demonstrate that the proposed transceiver realizes high resource efficiency, collision resolution capability, and reliability for smart railways mMTC over the LEO satellite.

Design and Concept of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems in Bangladesh

Bangladesh’s railway system mostly uses typical manual railway crossing techniques or boom gates through its 2955.53 km rail route all over the country. Accidents frequently happen at railway crossings due to the lack of quickly operating gate systems, and to fewer safety measures at the railway crossing as well. Currently, there are very few automatic railway crossing systems available (without obstacle detectors). Additionally, all of them are dependent on the national power grid, without a backup plan for any emergency cases. Bangladesh is still running a bit behind in generating enough power for its consumption; hence, it is not possible to have a continuous power supply at all times all over the countryside. We aim to design and develop a smart railway crossing system with an obstacle detector to prevent common types of accidents at railway crossing points. We use two infrared (IR) sensors to operate the railway crossing systems, which are controlled by an Arduino Uno. This newly designed level crossing system is run with the help of sustainable renewable energy, which is cost-effective and eco-friendly, and applied under the national green energy policy towards achieving sustainable development in Bangladesh as a part of the global sustainable goal to face climate change challenges. We have summarized the simulated the results of several renewable energy sources, including a hybrid system, and optimized the Levelized Cost of Energy (LCOE) and the payback periods.

Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

The networking of microgrids has received significant attention in the form of a smart grid. In this paper, a set of smart railway stations, which is assumed as microgrids, is connected together. It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid. Also, the operational costs of stations under various conditions decrease by applying the proposed method. The smart railway stations are studied in the presence of photovoltaic (PV) units, energy storage systems (ESSs), and regenerative braking strategies. Studying regenerative braking is one of the essential contributions. Moreover, the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method. The networked microgrid scheme of railway stations (based on coordinated operation and scheduling) and independent operation of railway stations are studied. The proposed method is applied to realistic case studies, including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company (TUSROC). The rolling stock is simulated in the MATLAB environment. Thus, the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming (MILP).

Optimal clustering-based operation of smart railway stations considering uncertainties of renewable energy sources and regenerative braking energies

The smart railway stations (SRSs), as prosumer microgrids, are considered active users in smart grids. By utilizing regenerative braking energy (RBE) and renewable energy resources (RERs) along with energy storage systems (ESSs), these SRSs can participate in the prosumer market. The uncertainties of RERs in SRSs due to meteorological factors have been studied in the literature. However, there is a research gap in developing a stochastic method for optimized operating of SRSs considering the RBE uncertainties besides the RER, load, and number of passengers’ uncertainties. In this paper, a new probabilistic clustering-based framework for the optimal operation of SRSs is presented. By applying Monte Carlo Simulations (MCS), several scenarios are generated and then clustered by the k-means algorithm. The introduced method is applied to an actual SRS in Tehran Urban and Suburban Railway Operation Company. The test results of the MCS, deterministic, and proposed scenario-based approaches are compared to illustrate the proposed method. Test results imply that the related error of the scenario-based method under the real-time pricing can be less than 4.4%, while the computation time significantly decreases. Furthermore, sensitivity analysis is done to determine how the exchanging power constraints and ESS capacity might influence the SRS operation.

Trajectory Optimization and Phase-Shift Design in IRS-Assisted UAV Network for Smart Railway

The recent trend towards the smart transportation system has spurred the development of the smart railway. However, enabling trains with seamless wireless connectivity using the roadside units (RSUs) is extremely challenging, mostly due to the lack of line of sight link. To address this issue, we propose a novel framework that uses intelligent reflecting surfaces (IRS)-enabled unmanned aerial vehicle (UAV) to provide line of sight communication to the smart railway system. First, we formulate the optimization problem where the objective is to maximize the minimum achievable rate of trains by jointly optimizing the trajectory of UAV and the phase-shift of IRS. Due to the non-convex nature of the formulated problem, it is decomposed into two subproblems: IRS phase-shift problem and UAV trajectory optimization problem. Next, a Binary Integer Linear Programming (BILP) and a Soft Actor-Critic (SAC) are constructed in order to solve our decomposed problems. Finally, comprehensive numerical results are provided in order to show the effectiveness of our proposed framework.

Cell Edge User Capacity-Coverage Reliability Tradeoff for 5G-R Systems With Overlapped Linear Coverage

Fifth-Generation mobile networks for Railway (5G-R) is a promising train-ground communication solution to deal with the design challenges on ubiquitous connections and high reliability transmission for smart railways. Considering the linear coverage scenario along the railway lines, deep overlapping coverage can enhance the coverage reliability, but the capacity of cell edge users is plagued by severe inter-cell interference. In this paper, the fundamental performance of 5G-R systems with linear redundant coverage is investigated. We quantitatively analyze the impact of inter-cell interference on the capacity of cell edge users, in which the exponential effective signal to interference plus noise (SINR) mapping method is utilized to analyze SINR distribution of 5G-R users. Then, we investigate the coverage reliability considering the base station (BS) failure. Finally, taking cell edge user capacity as the optimization objective, we analyze the cell edge user capacity-coverage reliability tradeoff for 5G-R systems, and then provide useful insights into BS deployment for 5G-R systems through performance simulations and numerical results.

“Smart railway station” — automation system of the railway station complex

The automation of control systems for life support processes and the provision of services at the infrastructure facilities of the passenger complex is considered. Digitization of borders, technologies, technical, technological and organizational processes involved in the provision of services for passengers, in the operation of station complexes, will make it possible to effectively manage engineering networks, minimizing gaps in the infrastructure and processes of transport systems.Causal relationships, algorithmization, mapping, data analysis, block diagramming, modeling, etc. are used. The main projects for the digital transformation of passenger facilities are identified, examples of local automated control systems for the life support processes of the station complex are given.The issue of automating feedback from passengers has been worked out separately, at the station complex, thanks to the information and reference telephone service, issues of a sanitary nature are centrally resolved. The proposed developments will make it possible to justify the development of technological areas within the frame-work of the Digital Railway program and the gradual transition from manual (personalized) labor at the station complex to an automated system during the modernization, reconstruction or introduction of local digital objects related to passenger service. As a result of these activities, it is expected to achieve the maximum efficiency of life support processes and the processes of rendering services of vault complexes.

Sensor Based Smart Railway Accident Detection and Prevention System for Smart Cities Using Real Time Mobile Communication

Sensor Based Smart Railway Accident Detection and Prevention System for Smart Cities Using Real Time Mobile Communication