Search Results (949)

Railway transportation has been integrated into people’s lives. According to the “Notice on the release of the General Technical Specification of High-speed Railway Power Supply Safety Testing (6C System) System” issued by the National Railway Administration of China in 2012, it is required to install pantograph and slide monitoring devices in high-speed railway stations, station throats and the inlet and exit lines of high-speed railway sections, and it is required to detect the damage of the slider with high precision. It can be seen that the good condition of the pantograph slider is very important for the normal operation of the railway system. As a part of providing power for high-speed rail and subway, the pantograph must be paid attention to in railway transportation to ensure its integrity. The wear of the pantograph is mainly due to the contact power supply between the slide block and the long wire during high-speed operation, which inevitably produces scratches, resulting in depressions on the upper surface of the pantograph slide block. During long-term use, because the depression is too deep, there is a risk of fracture. Therefore, it is necessary to monitor the slider regularly and replace the slider with serious wear. At present, most of the traditional methods use automation technology or simple computer vision technology for detection, which is inefficient. Therefore, this paper introduces computer vision and deep learning technology into pantograph slide wear detection. Specifically, this paper mainly studies the wear detection of the pantograph slider based on deep learning and the main purpose is to improve the detection accuracy and improve the effect of segmentation. From a methodological perspective, this paper employs a linear array camera to enhance the quality of the data sets. Additionally, it integrates an attention mechanism to improve segmentation performance. Furthermore, this study introduces a novel image stitching method to address issues related to incomplete images, thereby providing a comprehensive solution. Full article

Railway track defects pose significant safety risks and can lead to accidents, economic losses, and loss of life. Traditional manual inspection methods are either time-consuming, costly, or prone to human error. This paper proposes RailTrack-DaViT, a novel vision transformer-based approach for railway track defect classification. By leveraging the Dual Attention Vision Transformer (DaViT) architecture, RailTrack-DaViT effectively captures both global and local information, enabling accurate defect detection. The model is trained and evaluated on multiple datasets including fail, fastener and fishplate, multi-faults, and ThaiRailTrack. A comprehensive analysis of the model’s performance is provided including confusion matrices, training visualizations, and classification metrics. RailTrack-DaViT demonstrates superior performance compared to state-of-the-art CNN-based methods, achieving the highest accuracies: 96.9% on the rail dataset, 98.9% on the fastener and fishplate dataset, and 98.8% on the multi-faults dataset. Moreover, RailTrack-DaViT outperforms baselines on the ThaiRailTrack dataset with 99.2% accuracy, quickly adapts to unseen images, and shows better model stability during fine-tuning. This capability can significantly reduce time consumption when applying the model to novel datasets in practical applications. Full article

Any system for evaluating the safety service performance of heavy-haul railway lines must effectively reflect the real-time service status of the line. The working conditions of heavy-load lines are complex and diverse, particularly on uphill sections. Existing evaluation systems struggle to accurately reflect the service conditions of long and steep uphill sections bearing heavy loads, posing a significant threat to the safe operation of these lines. To address this problem, we propose a new method for evaluating the safety service performance of long and steep uphill sections of heavy-haul railway lines by establishing a scoring system based on the Analytic Hierarchy Process (AHP). First, damage indicators for heavy-haul lines are categorized into three groups: track geometry status indicators, track structure status indicators, and track traffic status indicators. Using data from existing heavy-haul lines and maintenance experiences, we determine a score deduction standard, classifying lines into four levels based on their safety service quality. Next, we establish a coefficient table for the service performance of long and steep uphill sections after the corresponding scores are deducted. Using data for the length and elevation grade of the actual uphill section, we adjust the deducted scores of the track structure status indicators, enhancing the evaluation system’s accuracy in describing the working conditions. Finally, we verify the stability of the entire system by conducting a sensitivity analysis of the indicator evaluation results using the One-At-a-Time (OAT) method. This method fills a critical gap in the safe operation and maintenance of heavy-haul railways and provides a safety guarantee for the operation of long uphill sections of heavy-haul railways. Full article

Higher efficiency of rail transportation at the present stage of development of the transport industry necessitates the creation and introduction of rail vehicles with improved technical and economic characteristics among which is reduced tare weight. The issue of reducing the tare weight of wagons is quite urgent. It deals not only with the sprung mass of the wagon but also with the load on the rail track, which is under the influence of constant cyclic loads. Therefore, the present study deals with the development of a wagon covered with tarpaulin for carrying goods requiring protection against the environment. The loads inherent for operation on 1520 mm gauge lines are considered. The covered wagon mod. 11-217 is chosen as a prototype. The profiles of the covered wagon frame components are selected according to the moment of resistance of their cross-sections. It is found that the proposed design has a 16% lower tare weight than that of the prototype. The results of the strength calculation for the wagon under the main design operating modes have proved the feasibility of its structural design. The motion of the covered wagon over a track irregularity has been assessed as ‘excellent’. The results of the study will contribute to the creation of recommendations for the development of modern structures of covered wagons as well as improve the efficiency of railway transportation. Full article

Rail traction and resistance play an essential role in the efficient operation of rail systems. The nature of traction is based on the balance between static friction and generated force at the perimeter of the driving wheels. The main objective of this paper is the development of a methodology and a modeling procedure for the design of train speed trajectory diagrams for the suburban railway. The model is applied to the Athens–Chalkida railway line (in Greece). For this purpose, geometric data for the above-mentioned railway line is collected from the Hellenic Railways Organization (OSE) and then recorded and digitized. A code is developed in MATLAB to calculate the total resistance of the railway line at each kilometer position. The traction elements of the trains operating on the Athens–Chalkida–Athens line, as well as other representative trains, and the magnitudes of their mechanical-aerodynamic resistances are recorded. The MATLAB program generates and compiles the train speed trajectory diagrams and the traction-resistance matrices. Finally, a comparison is made between the time, energy, CO₂ emissions, and fuel costs of the rail in relation to the competing mode of transportation, which, for the specific line studied, is the tourist bus. Full article

This paper addresses the challenge of detecting unknown or unforeseen obstacles in railway track transportation, proposing an innovative detection strategy that integrates an incremental clustering algorithm with lightweight segmentation techniques. In the detection phase, the paper innovatively employs the incremental clustering algorithm as a core method, combined with dilation and erosion theories, to expand the boundaries of point cloud clusters, merging adjacent point cloud elements into unified clusters. This method effectively identifies and connects spatially adjacent point cloud clusters while efficiently eliminating noise from target object point clouds, thereby achieving more precise recognition of unknown obstacles on the track. Furthermore, the effective integration of this algorithm with lightweight shared convolutional semantic segmentation algorithms enables accurate localization of obstacles. Experimental results using two combined public datasets demonstrate that the obstacle detection average recall rate of the proposed method reaches 90.3%, significantly enhancing system reliability. These findings indicate that the proposed detection strategy effectively improves the accuracy and real-time performance of obstacle recognition, thereby presenting important practical application value for ensuring the safe operation of railway tracks. Full article

This paper shows the usage of a numerical analysis model that enables the calculation of the life of railway wheels used for low-floor freight wagons as a function of its primary operating factors, which allows for carrying out sensitivity analyses. Low-floor wagons are being increasingly used for combined transport applications, and many types of bogies have been proposed to constitute the wagons. Due to the uniqueness of this type of wagon, the bogie configurations in terms of wheelbase and axle load have hardly been analyzed so far. The numerical analysis model used addresses the primary challenges that arise in the vehicle–track interaction and establishes the relations among them. The main aspects of this model have been described in this paper, which has been later used to calculate the life of an ordinary-diameter wheel for several wheelbase and axle load values. This study has been replicated with reduced-diameter wheels, which are commonly used for low-floor wagons. In this way, it is possible to know the evolution of the life depending on the wheelbase and the axle load. The observed behaviors are not so dissimilar for the different types of wheels, and they point out huge increases in wear as the axle load and the wheelbase rise, especially with axle load. The root causes can be explained by the entire understanding of the rolling phenomenon provided by the full analytical work. Full article

The growing relevance of promoting a transition of urban mobility toward more sustainable modes of transport is leading to efforts to understand the effects of the built environment on the use of railway systems. In this direction, there are challenges regarding the creation of coherence between the locations of metro stations and their surroundings, which has been explored extensively in the academic community. This process is called Transit-Oriented Development (TOD). Within the context of Latin America, this study seeks to assess the influence of the built environment on the metro ridership in the metropolitan area of Valparaíso, Chile, testing two approaches of influence area definition, one of which is a fixed distance from the stations, and the other is based on the origin and destination survey of the study area. The analysis is based on Ordinary Least Squares regression (OLS) to identify the factors from the built environment, which affects the metro’s ridership. Results show that the models based on the area of influence defined through the use of the origin and destination survey explain the metro ridership better. Moreover, this study reveals that the metro system in Greater Valparaíso was not planned in harmony with urban development. The models demonstrate an inverse effect of the built environment on ridership, contrasting with the expected outcomes of a metro station designed following a Transit-Oriented Development approach. Full article

This study aims to elucidate the implications of carbon peak and carbon neutrality targets on corridor logistics, with a focus on the burgeoning high-speed rail express sector. Acknowledging carbon emissions taxation as an integral component of transportation costs, it examines the competitive dynamics among four cargo transport modes: high-speed rail (HSR), conventional rail, aviation, and road transport. Within a strategic game framework, carriers are analyzed based on freight rates, speed, safety, reliability, and convenience to assess their utility. A dynamic game model and a solution approach are developed, aiming to optimize freight-related variables, maximize carriers’ generalized profits, and enhance shippers’ utility. Empirical validation is provided through case studies in Xi’an and Lanzhou, northwest China, affirming the model’s efficacy. The findings reveal the strong competitive edge of the high-speed rail express in the corridor, offering valuable insights for carrier pricing strategies, emission tax rate setting, and macro-policy adjustments in the transport sector. Full article

Measuring the accessibility of each traffic zone to high-speed railway stations can evaluate the ease of the transportation hub in the transportation system. The utility-based model, which captures individual travel behavior and subjective perception, is often used to quantify the travel impedance on accessibility for a given origin–destination pair. However, existing studies neglect the impacts of travel time uncertainty on utility and possible choice set when measuring accessibility, especially in high-timeliness travel (e.g., railway stations or airports). This study proposes a novel integration of the utility-based model and multimodal space–time prism under travel time uncertainty to measure reliable accessibility to high-speed railway stations. First, the reliable multimodal space–time prism is developed to generate a reliable travel mode choice set constrained by travel time budgets. Then, the reliable choice set is integrated into the utility-based model with the utility function derived from a proposed mean–standard deviation logit-based mode choice model. Finally, this study contributes to measuring reliable accessibility within areas from Beijing’s 5th Ring Road to the Beijing South Railway Station. Based on the results, policymakers can effectively evaluate the distribution of transportation resources and urban planning. Full article

This study focuses on the ‘short-inverted transportation’ scenario of intermodal transport. It proposes a vehicle unloading reservation mechanism to optimize the point-of-demand scheduling system for the inefficiency of transport due to the complexity and uncertainty of the scheduling strategy. This paper establishes a scheduling strategy optimization model to minimize the cost of short backhaul and obtain the shortest delivery time window and designs a hybrid NSGWO algorithm suitable for multi-objective optimization to solve the problem. The algorithm incorporates the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm based on the Grey Wolf Optimizer (GWO) algorithm, compensating for a single algorithm’s premature convergence. The experiment selects a logistics carrier’s actual road–rail intermodal short-inverted data and compares and verifies the above data. The results show that the scheduling scheme obtained by this algorithm can save 41.01% of the transport cost and shorten the total delivery time by 46.94% compared with the original scheme, which can effectively protect the enterprise’s economic benefits while achieving timely delivery. At the same time, the optimized scheduling plan resulted in a lower number of transport vehicles, which positively impacted the sustainability of green logistics. Full article

A planned interruption of railway infrastructure is a situation where the operation of the track line or the operation of railway transport is limited. If there is also a restriction on the railway infrastructure, it means there will be complications not only for passengers but, above all, for railway undertakings operating freight transport. However, because of the planned railway infrastructure interruption, the quality of services provided not only to passengers but also to freight transport is decreasing. The aim of this paper is to propose effective planned maintenance works based on the analysis and evaluation of the processes performed during the planned railway infrastructure interruption or restriction. The research describes the process of affected railway infrastructure from technical, cost, and safety points of view. A methodological procedure is proposed under the condition of the Czech infrastructure manager. The main method is the calculation of the costs for the railway infrastructure manager and railway operator during the infrastructure interruption. The application part is undertaken using two interrupted lines according to the established alternative timetable in the area of České Budějovice. Full article

Aiming at the operational efficiency of small farm machinery groups in cooperative operations in hilly areas, this study proposes a static task allocation model. This method combines the optimal gene fragment retention method based on a genetic algorithm (OGFR-GA) and the method for generating multi-loop weighted connected graphs based on Prim’s algorithm (MLW-Prim). The collaborative objective function for the harvester group was established by considering factors such as operation time, fuel consumption, and distance. The OGFR-GA was designed and applied multiple times to obtain several optimal gene fragments corresponding to the number of farm machines. These fragments were used as critical paths in the weighted connected graph generated based on farm machinery performance parameters and task parameters. The MLW-Prim method was proposed to construct this weighted connected graph and realize the static task allocation model for multi-machine cooperative operations. Simulation experiments showed that the model combining OGFR-GA and MLW-Prim achieved optimal values with fewer iterations, and reduced both group cost and cost variance compared to traditional algorithms. This method meets the static task allocation needs for multi-machine cooperative operations in agricultural production and can be integrated with intelligent operations in mountainous and hilly regions, laying a theoretical foundation for improving efficiency. Full article

Historical transportation infrastructures (HTIs) like railways and bridges are essential to our cultural heritage. However, the preservation and enhancement of these structures pose significant challenges due to their complex nature and the need for modern upgrades. Historic building information modeling (HBIM) has emerged as a solution, facilitating the documentation, restoration, and maintenance of historic transportation assets. The purpose of the proposed work is to provide a systematic review of research findings on the application of HBIM in historic transportation infrastructure, highlighting its role in capturing intricate architectural details and supporting decision making for preservation efforts. A series of case studies in which HBIM has been instrumental in preserving historic transportation infrastructure are investigated and analyzed using a comprehensive literature review method. Furthermore, future directions in HBIM research are proposed, identifying potential applications and recommending areas for further investigation. Additionally, this paper suggests HBIM’s potential to balance modernization demands with the conservation needs of historic transportation infrastructure, providing policymakers and stakeholders with insightful strategies for sustainable heritage management. Full article

Climatic changes have intensified heavy rainfall events in India, causing daily downpours from 156 to 594 mm, and these are expected to worsen in the future. This study analyses a double-line railway embankment using transient unsaturated–saturated seepage analysis through numerical modeling to examine the impact of rainfall scenarios, embankment height, initial groundwater table position, and soil water characteristics curves (SWCCs) of subgrade and subsoil. Our findings indicate an increased vulnerability of embankments to future rainfall due to rapid increases in the groundwater level, necessitating the requirement to make railway embankments resilient to climate change and thereby offering a sustainable mode of transportation. The groundwater onset mechanism across different heights remained consistent; rainwater infiltrated through side slopes first, rose near the toe, and then flowed horizontally, leading to convergence. The convergence level is affected by the SWCCs; however, a single normalized convergence plot can be created by presuming the horizontal flow of the infiltrated water through embankment and subsoil, irrespective of the material type, establishing horizontal flow as the principal convergence mechanism. In embankments over low-permeability subsoil, extremely heavy rainfall creates a unique pattern: side slopes and the top saturate early, while the saturation of the bottom central part is delayed. In such cases, deriving a groundwater variation curve might be challenging. Full article