Search Results (79)

Establishing a high-precision passenger flow prediction model is a critical and complex task for the optimization of urban rail transit systems. With the development of artificial intelligence technology, the data-driven technology has been widely studied in the intelligent transportation system. In this study, a neural network model based on the data-driven technology is established for the prediction of passenger flow in multiple urban rail transit stations to enable smart perception for optimizing urban railway transportation. The integration of network units with different specialities in the proposed model allows the network to capture passenger flow data, temporal correlation, spatial correlation, and spatiotemporal correlation with the dual attention mechanism, further improving the prediction accuracy. Experiments based on the actual passenger flow data of Beijing Metro Line 13 are conducted to compare the prediction performance of the proposed data-driven model with the other baseline models. The experimental results demonstrate that the proposed prediction model achieves lower MAE and RMSE in passenger flow prediction, and its fitted curve more closely aligns with the actual passenger flow data. This demonstrates the model’s practical potential to enhance intelligent transportation system management through more accurate passenger flow forecasting. Full article

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article

This paper aims to present a hybrid steering control method combining the self-guidance capability of a wheelset and fuzzy logic controller (FLC), which were applied to our new micro-autonomous railway inspection vehicle, enhancing the vehicle’s stability. The vehicle features intelligent inspection systems and a suspension system with variable damping capability that uses smart magnetorheological fluid to control vertical oscillations. A mathematical model of the steering dynamic system was developed based on the vehicle’s unique structure. Two simulation models of the vehicle were built on Simpack and Simulink to evaluate the lateral dynamic capability of the wheelset, applying Hertzian normal theory and Kalker’s linear theory. The hybrid steering control was designed to adjust the torque differential of the two front-wheel drive motors of the vehicle to keep the vehicle centered on the track during operation. The control simulation results show that this hybrid control system has better performance than an uncontrolled vehicle, effectively keeps the car on the track centerline with deviation below 10% under working conditions, and takes advantage of the natural self-guiding force of the wheelset. In conclusion, the proposed hybrid steering system controller demonstrates stable and efficient operation and meets the working requirements of intelligent track inspection systems installed on vehicles. Full article

The development of cost-effective and reliable railway monitoring technologies is crucial for the maintenance of modern infrastructure. Embedding sensors into rail pads has emerged as a promising approach for monitoring wheel–track interactions, but the successful implementation of these systems requires a robust framework for signal data acquisition and analysis. This study validates a custom-designed External Signal Acquisition Device (ESAD) for use with smart rail pads, comparing its performance against a high-precision commercial analog module. While the commercial module delivers exceptional accuracy, its high cost, bulky size, and complex installation requirements limit its practicality for large-scale railway applications. Laboratory-scale and full-scale experiments simulating real-world railway conditions demonstrated that the custom ESAD performs comparably to the commercial module. During simulated train passages, the ESAD showed reduced signal dispersion as load and train speed increased, confirming its ability to provide reliable calibration data. Moreover, the device maintained over 95% reliability in analyzing load-to-signal linearity, ensuring consistent and dependable performance in both laboratory and field settings. However, the ESAD does have limitations, including slightly lower resolution for low frequencies and potential sensitivity to extreme environmental conditions, which may affect its performance in specific scenarios. These findings highlight the ESAD’s potential to strike a balance between cost and functionality, making it a viable solution for widespread railway monitoring applications. This research contributes to the advancement of affordable and efficient railway monitoring technologies, fostering the adoption of preventive maintenance practices and enhancing overall infrastructure performance. Full article

Advancements in transport engineering and technology play a crucial role in improving multimodal transport systems and optimizing logistics operations. This study focuses on efficient material flow management in an industrial enterprise, directly supporting the goals of sustainable transport and innovative logistics strategies. The manufacturing plant in Veselí nad Lužnicí was selected as a case study because of the identified inefficiencies in its logistics processes and the availability of detailed operational data, allowing for an accurate analysis of material flows. The research identifies weaknesses in the current material flow and proposes the following two optimization solutions: replacing an external operator for semi-finished goods transport with in-house logistics and substituting external transport providers for finished goods transportation with an internally managed fleet. The proposed methodology introduces a novel integration of analytical tools, including checkerboard table analysis, cost modeling, and return-on-investment (ROI) assessment, to evaluate logistics efficiency and minimize material handling costs. This study demonstrates how optimized material flows, particularly using railway logistics, can contribute to cost-effective and sustainable supply chains. The research reflects current trends in transport system planning, emphasizing transport modeling, digital twin simulations, and smart railway technologies to enhance operational efficiency and resilience. The results provide practical recommendations for companies seeking to integrate rail transport into their logistics processes, contributing to broader objectives of environmental sustainability and digital transformation in the transport sector. Full article

With the advent of Industry 4.0, the seamless integration of industrial systems and unmanned technologies has significantly accelerated the development of smart industries. However, the research on task allocation for railway maintenance robots remains limited, particularly with respect to optimizing costs and efficiency within smart railway systems. To address this gap, the present study explores multi-robot task allocation for automated orbital bolt maintenance, aiming to enhance operational efficiency by minimizing both makespan and total travel distance for all robots. To achieve this, an improved hybrid algorithm combining NSGA-II and MOPSO is proposed. Initially, a dynamic task planning method, tailored to the specific conditions of railway operations, is developed. This method uses the coordinates of track bolts to extract environmental features, enabling the dynamic partitioning of task areas. Subsequently, a multi-elite archive strategy is introduced, along with an adaptive mechanism for adjusting crossover and mutation probabilities. This ensures the preservation and maintenance of multiple solutions across various Pareto fronts, effectively mitigating the premature convergence commonly observed in traditional NSGA-II algorithms. Moreover, the integration of the MOPSO algorithm strikes a balance between local and global search capabilities, thereby enhancing both optimization efficiency and solution quality. Finally, a series of experiments, conducted with varying task sizes and robot quantities during the railway maintenance window, validate the effectiveness and improved performance of the proposed algorithm in addressing the multi-robot task allocation problem. Full article

Historically, railway facilities have been intertwined with daily life, communities, geography, and history, contributing to a rich cultural heritage and collective memory. However, current research on railway reuse primarily focuses on converting railway architecture into artistic displays, with limited exploration of urban railway revitalization. Addressing the challenges of urban railroads requires reevaluating space reuse models. Therefore, local revitalization has emerged as a key driver of society. We empirically explored the benefits of reusing urban old railroads from the perspective of local revitalization using the SMART Ecological Innovation Framework in revitalizing old railroads. We identified five forces: storytelling, market sensibility, aesthetics, regeneration, and local cultural design. Measurement items for these concepts were assessed using a five-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). With a solid theoretical foundation, we employed confirmatory factor analysis to affirm the reliability and validity of these concepts, ensuring their stability. This study aimed to delve into regenerating old railways in Taichung City and explore the reuse benefits of urban railways to offer valuable insights for similar cases. The confirmatory factor analysis result revealed that storytelling, market perception, aesthetics, regeneration capability, and local design significantly contributed to the benefits of railway revitalization. Furthermore, the concept of local revitalization was effectively applied through these five forces in planning and design, stimulating economic development in idle areas. Full article

The seismic response detection and operational safety assessment of high-speed railway (HSR) bridges play a crucial role in ensuring HSR systems’ operational safety and reliability. Smartphones have introduced intelligent inspection tools for structural health detection, becoming a new tool for intelligent structural inspection. Combining the public and smartphones is the key to public participation in structural health detection. This study utilizes smartphone-based structural seismic response inspection technology to investigate the framework of public participation in earthquake response inspection and assessment. This system comprises the Smart Bridge Brain (SBB), which integrates data from multiple sources and systems, an assigning mechanism for public participation inspection tasks, and smartphone-based HSR bridge structural seismic response inspection technology. At the same time, the Unreal Engine 5.0 software is used to create a mixed-reality virtual simulation experimental environment to validate the feasibility of this framework. The results indicate that the intelligent optimization of task allocation by the SBB successfully assigns detection tasks to each public participant. Public participants can promptly reach predefined damage structure detection targets and rapidly inspect bridge structural seismic response indicators using smartphones. In addition, this paper also conducts a comprehensive evaluation and analysis of the detection of the work efficiency index (WEI) within the system. Furthermore, optimization strategies for the efficient execution of detection tasks are proposed based on WEI variations influenced by different factors. The system framework is expected to enhance cluster-based HSR bridges’ intelligent disaster prevention and mitigation capabilities. Full article

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%. Full article

Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous obstacle detection in railways is a critical aspect of railway safety and operation. While the widespread deployment of autonomous obstacle detection systems is still under consideration, the ongoing advancements in technology and infrastructure are paving the way for their full implementation. The SMART2 project developed a holistic obstacle detection (OD) system consisting of three sub-systems: long-range on-board, trackside (TS), and Unmanned Aerial Vehicle (UAV)-based OD sub-systems. All three sub-systems are integrated into a holistic OD system via interfaces to a central Decision Support System (DSS) that analyzes the inputs of all three sub-systems and makes decision about locations of possible hazardous obstacles with respect to trains. A holistic approach to autonomous obstacle detection for railways increases the detection area, including areas behind a curve, a slope, tunnels, and other elements blocking the train’s view on the rail tracks, in addition to providing long-range straight rail track OD. This paper presents a demonstration of the SMART2 holistic OD performed during the operational cargo haul with in-service trains. This paper defines the demonstration setup and scenario and shows the performance of the developed holistic OD system in a real environment. Full article

In recent years, there has been increasing interest in integrating the smart grid concept into railway networks, which has been driven by the need to enhance energy efficiency and reduce air pollution in such energy-intensive systems. Consequently, experts have actively sought innovative solutions with which to tackle these challenges. One promising strategy involves integrating renewable energy sources (RESs), energy storage systems (ESSs), and electric vehicle charging stations (EVCSs) into current electric railway systems (ERSs). This study begins by examining the concept of implementing smart grids in railway systems through bibliometric analysis. It then delves into the realization of a hybrid railway microgrid (H-RMG) designed to enhance power flow capacities, improve energy efficiency, and address power quality issues in traditional AC railway networks. This paper introduces various future AC–DC-coupled hybrid railway microgrid (ADH-RMG) architectures centered around a shared DC bus acting as a DC hub for upgrading conventional AC railway systems utilizing interfacing static converters. Through an exploration of different possible ADH-RMG configurations, this research aims to offer valuable insights and a roadmap for the modernization and reconstruction of existing railway networks using smart grid technologies. The integration of RESs and EV charging infrastructures within the ADH-RMG concept presents a promising pathway toward establishing more sustainable and environmentally friendly railway systems. Full article

A pantograph is a key component on the tops of trains that allows them to efficiently tap electricity from power lines and propel them. This study investigates the possibility of using metal matrix composites (MMCs), specifically aluminum MMCs, as a material for making pantograph parts regarding the dynamics of the train’s movement and external meteorological conditions. In this study, a computer-aided design (CAD) model is created using PTC Creo design software and moves to detailed finite element analysis (FEA) simulations executed by the ANSYS software suite. These simulations are important in examining how the dynamic performance of pantographs can vary. The incorporation of Al MMC materials into the structure of the pantograph resulted in significant improvements in structural robustness, with equal stress reduced by up to 0.18%. Similarly, aluminum MMC materials reduced the strain energy by 0.063 millijoules. The outcomes not only give a new perspective to the implementation of modern materials but also provide a breakthrough concept to improve efficiency and increase the service life of pantographs. This study marks a significant milestone in the theoretical development of essential train systems, furnishing eminent perspectives toward the tactical development of transportation infrastructure by suggesting new avenues for the smooth incorporation of smart materials in railway transportation, which would contribute to a more sustainable and reliable future. Full article

The integration of a renewable energy and hybrid energy storage system (HESS) into electrified railways to build an electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the effectiveness of the energy management for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow in the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study. Full article

Rail is expected to become the backbone of future mobility in the world as the cleanest and greenest high-volume transport. Rail generates the lowest CO₂ emissions and energy consumption when in operation, with respect to the other transportation modes, but during construction and maintenance phases, its environmental impacts are significant and need to be carefully assessed and properly mitigated. This paper, through an extensive analysis of the recent literature, aims to provide a comprehensive framework of trends and challenges in railway sustainability, with particular attention paid to track and related materials and components, maintenance strategies, and methods of assessment of sustainability. The followed approach takes into consideration the lifespan of the track and the related main stages. The results show that: (i) several innovative sustainable materials have been introduced with significant environmental performances and limitations, mainly due to the lack of knowledge of long-term mechanical behavior; (ii) appropriate strategies of maintenance, supported by effective monitoring of the track conditions, can reduce negative effects on the environment and society and contribute to making this transportation mode greener; (iii) many devices for the automated detection of the track defects allow increasingly widespread and effective monitoring of the track and are essential means in overcoming the challenge of “smart rails”; and (iv) life cycle assessment (LCA) and circularity metrics are effective and indispensable tools in the decision-making process, since they help to quantify the potential environmental enhancement of different materials and solutions. Full article

This article presents a review of cutting-edge technologies poised to shape the future of railway transportation systems, focusing on enhancing their intelligence, safety, and environmental sustainability. It illustrates key aspects of the energy-transport-information/communication system nexus as a framework for future railway systems development. Initially, we provide a review of the existing challenges within the realm of railway transportation. Subsequently, we delve into the realm of emerging propulsion technologies, which are pivotal for ensuring the sustainability of transportation. These include innovative solutions such as alternative fuel-based systems, hydrogen fuel cells, and energy storage technologies geared towards harnessing kinetic energy and facilitating power transfer. In the following section, we turn our attention to emerging information and telecommunication systems, including Long-Term Evolution (LTE) and fifth generation New Radio (5G NR) networks tailored for railway applications. Additionally, we delve into the integral role played by the Industrial Internet of Things (Industrial IoT) in this evolving landscape. Concluding our analysis, we examine the integration of information and communication technologies and remote sensor networks within the context of Industry 4.0. This leveraging of information pertaining to transportation infrastructure promises to bolster energy efficiency, safety, and resilience in the transportation ecosystem. Furthermore, we examine the significance of the smart grid in the realm of railway transport, along with the indispensable resources required to bring forth the vision of energy-smart railways. Full article