Search Results (35)

Railway utilities play a vital role as social infrastructure, i.e., as an essential part of ordinary citizens’ lives. In this study, we aimed to evaluate the performance of railway utility activities in Japan from three perspectives: financial management, facility operations, and human resources. Examining the relationship between daily passenger kilometers and passenger kilometers across six JR (Japan Railways) companies, we found that they can be divided into two groups: Group A, located in urban areas with higher passenger demand, and Group B, located in rural areas with lower passenger demand. We further found that the passenger demand of JR companies can be captured by a single nonlinear mathematical model. We used this mathematical model to investigate passenger demand composition in terms of commuters/non-commuters and then proposed strategies to increase passenger demand. We applied a cluster analysis technique to classify the set of JR and major private railway companies into four clusters, characterizing the performance of the railway utilities within each cluster and highlighting similarities and differences among them. Then, we applied principal component analysis and selected three principal components to explain the performance of Japanese railway utility activities. We found that the first component represents an axis corresponding to comprehensive factors that improve the performance of railway utilities from the viewpoints of both revenue and financial balance, while the second component represents an axis related to the profit and cost for railway utilities from the viewpoint of financial balance. Through multivariate regression model analyses, we found factors that increase total revenue from Japanese railway utility activities: higher passenger numbers, longer passenger transport distance, and fewer staff. Full article

The imbalance of urban public transport networks often leads to traffic congestion. Traditional planning prioritizes system optimization and single-mode travel, neglecting interactions between different modes. From an economic perspective and based on passenger travel behavior, this paper constructs a reasonable path set for multimodal networks. Using information entropy, it establishes multidimensional indicators including site path diversity entropy, destination regional entropy vectors, and weighted comprehensive entropy. Regional aggregation and coefficient of variation analyze internal balance, while scatter plots and the Gini coefficient measure global resource allocation equity. ArcGIS Pro 3.4.3 is employed for spatial analysis and visualization. An empirical study of Beijing’s six central districts reveals significant spatial heterogeneity in path distribution across functional zones: working areas exhibit concentric patterns, commercial areas form corridor agglomerations, residential areas have the highest entropy values, and transport hubs are relatively balanced. Cluster analysis based on entropy vectors effectively identifies commuter, residential, and hub station types. Some hubs show an ideal “high richness, low imbalance” state, while areas like Beijing Railway Station exhibit “low richness, high imbalance.” The Gini coefficient of 0.1864 indicates relatively balanced public transport resources overall. The “route-region-demand” collaborative analysis framework constructed in this study achieves a paradigm shift from static network structure to dynamic human-oriented evaluation, providing methodological support for equity assessment, network optimization, and resource allocation in multimodal public transport networks, and can contribute to the equitable and balanced sustainable development of public transport. Full article

In this paper, the task of detecting bearing faults in railway vehicles during regular operation by analyzing acoustic (airborne sound) data is addressed. To that end, various features are studied, among which the Mel Frequency Cepstral Coefficients (MFCCs) are best suited for detecting bearing faults by analyzing airborne sound. The MFCCs are used to train a Multi-Layer Perceptron (MLP) classifier. The proposed method is evaluated with real-world data for a state-of-the-art commuter railway vehicle in a dedicated measurement campaign. Classification results demonstrate that the chosen MFCC features allow for reliable detection of bearing damages, even for damages that were not included in training. Full article

As a core factor in advancing urban agglomeration development and new urbanization, the structural resilience of multi-modal transportation networks in metropolitan areas directly determines their disturbance resistance during emergencies and their sustainable development. To address the prevalent “core–peripheral” connectivity imbalance in medium-sized metropolitan areas, this study takes the Jinan Metropolitan Area as an empirical case to systematically explore its multi-modal transportation network’s structural resilience. A three-dimensional evaluation framework of “absorbing capacity–buffering capacity–recovery capacity” was built based on complex network theory. Network efficiency was used to measure absorbing capacity, the average number of independent paths was used to characterize buffering capacity, and structural entropy was used to determine recovery capacity. The entropy weight method was used to calculate integrated multi-dimensional resilience values, and a sequential node failure simulation was used to analyze network invulnerability. The main findings are as follows: (1) The Jinan Metropolitan Area’s multi-modal transportation network has “small-world characteristics” but low density, with trunk line coverage gaps. (2) Sub-networks differ significantly. The railway sub-network performs best, the highway sub-network is the weakest, and the composite network achieves resilience balance through multi-modal collaboration. (3) Node failure analysis reveals that “core hubs are resilience pillars, while secondary highway nodes are weaknesses.” The proposed “three-dimensional evaluation framework” provides a methodological reference for resilience quantification in similar metropolitan areas, and the “trunk line densification + peripheral connection” strategy supports the implementation of metropolitan planning policies to promote modern metropolitan transportation systems with efficient commuting and robust disturbance resistance. Full article

Railway barrier drives are key components of railway infrastructure and have a direct impact on traffic safety. Many of the commonly used drives are mechanical EEG-type barrier drives. EEG is a commercial designation of level-crossing gate drives produced by one of the Polish railway signalling equipment manufacturers, currently known as Alstom ZWUS Polska Sp. z o.o. (Katowice, Poland). These drives are characterized by their simple design and low cost, but limited efficiency and durability. Operational experience shows particular problems with the operation of this type of drive in winter conditions. This article presents an analysis of the impact of the selection of electric motors on the efficiency and reliability of level crossing drives. In addition to discussing the classic design with a PRMOa90-90 motor, commonly used in EEG drives, two proprietary solutions are presented: a commutator motor with rectangular neodymium magnets and a brushless DC motor (BLDC). Key operating parameters such as energy efficiency, starting torque, durability, maintenance requirements, and costs were compared. The results of the analyses indicate that the use of motors with neodymium magnets and BLDC solutions can significantly increase the efficiency and reliability of barrier drives, with each variant presenting a different profile of advantages and limitations. Full article

Urban livability and sustainable development remain major global challenges, yet the interplay between urban planning layouts and actual human activities has not been sufficiently examined. This study investigates this relationship in Beijing by integrating multi-source spatiotemporal data, including point of interest (POI), Land Use Cover Change (LUCC), remote sensing data, and the railway network. Defining urban functional units as “street + railway network”, we analyze the spatial–temporal evolution within the 6th Ring Road over the past four decades and propose targeted strategies for the urban functional layout. The results reveal the following: (1) The evolution of Beijing’s urban functions can be divided into four stages (1980–1990, 1990–2005, 2005–2015, and 2015–2020), with continuous population growth (+142%) driving the over-concentration of functions in central districts. (2) Between 2010 and 2020, the POI densities of medical services (+133.6%) and transport services (+130.48%) increased most rapidly, subsequently stimulating the expansion of other urban functions. (3) High-density functional facilities and construction land (+179.10%) have expanded significantly within the 6th Ring Road, while green space (cropland, forestland and grassland) has decreased by 86.97%, resulting in a severe imbalance among land use types. To address these issues, we recommend the following: redistributing high-intensity functions to sub-centers such as Tongzhou and Xiongan New Area to alleviate population pressure, expanding high-capacity rail transit to reinforce 30–50 km commuting links between the core and periphery, and establishing ecological corridors to connect green wedges, thereby enhancing carbon sequestration and environmental quality. This integrated framework offers transferable insights for other megacities, providing guidance for sustainable functional planning that aligns human activity patterns with urban spatial structures. Full article

The metro railway system is pivotal not just as a crucial transportation network for daily commuters but also as a significant enhancer of urban vibrancy, especially through its role in attracting a substantial volume of non-commuters. This study focuses on non-commuting travel behaviors around metro stations, exploring how the built environment affects non-commuters’ destination choices. A Random Forest model is developed based on data from Chengdu, China. The model is interpreted with SHapley Additive exPlanations (SHAP) analysis. Route length, building coverage, greenery, and proximity are key factors and indicate a nonlinear impact on non-commuters’ destination choices. The impact of these factors was found to vary significantly depending on the scale and context, indicating a need for nuanced urban planning approaches. The findings highlight the need for sophisticated urban planning that balances functionality and needs in transit-oriented development, aiming to cater to non-commuters and promote sustainable, vibrant urban spaces. Full article

Budapest and its metropolitan area serve as a key railway hub both within Hungary and across Europe, intersected by multiple European rail corridors and characterized by substantial suburban traffic driven by daily commuters from surrounding areas. The Budapest agglomeration is served by 11 rail lines to Budapest managed by the MÁV Group Company (MÁV: Magyar Államvasutak Co., Budapest, Hungary) is a railway company owned by the Hungarian state). The majority of these are high-capacity, mostly double-track electrified main lines, which play a major role in long-distance and international transport. The main goal of the MÁV Group Company is the continuous development of the quality of passenger transport in Hungary and Europe, quality improvement in passenger comfort, sales, and passenger information systems, and the introduction of up-to-date, environmentally friendly means and solutions. Infrastructure plays a decisive role in the development and transformation of the country and its regions, municipalities, and settlement systems. The development of transport infrastructure not only dynamically transforms and shapes spatial structures but also initiates processes of internal differentiation. In our study, statistical analysis of municipalities and rail-based public transport confirmed a positive correlation between the modernization of transport infrastructure and selected demographic indicators. Full article

Exploring the relationship between land use characteristics and ridership in railway station areas provides crucial decision-making support for station area planning. Previous research has mostly focused on subways, with a lack of studies on the land use characteristics and ridership of commuter rail stations, particularly in relation to the differences and impacts across various passenger catchment areas (PCAs). This study employed a multinomial logit model to evaluate the land use characteristics within 1000 m of Japan Railways (JR) stations in four different PCAs of the Tokyo metropolitan area (TMA). Additionally, regression models and a multiscale geographically weighted regression (MGWR) model were used to analyze how land use characteristics in these PCAs affected station ridership. The key findings were as follows: (1) the land use characteristics around commuter rail stations exhibit distinct zonal patterns; within 250 m, public transport stops and public service facilities are the most densely concentrated; the highest residential population density is found between 250 and 750 m; and commercial facilities are mostly clustered in the 500 to 750 m range; (2) the impact of land use factors on ridership varies in intensity across different spatial zones; the density of public transport stops and street network density is most significant within 250 m, whereas commercial facility density is greatest within the 500–750 m PCA; (3) The land use characteristics within 500 m of stations have greater explanatory power for passenger flow, and the goodness of fit of the MGWR model surpasses that of the linear regression model. Full article

In today’s digital society, social networks such as Twitter are a preferred place for expressing one’s emotions, especially when they are negative. Despite a growing interest in the variety of linguistic realizations of commuters’ complaints, little attention has so far been paid to writers’ choices, especially when morphologically or syntactically simpler alternative formulations are available. A typical example is the “inference towards the antonym” triggered by the negation of contrary adjectives, an effect that is stronger for positive compared to negative adjectives. In the context of railway transport, a customer could use the negative statement The train is not clean instead of the corresponding affirmative sentence The train is dirty. It remains unclear, in our current state of knowledge, why online customers would prefer more complex constructions to voice their criticisms. Based on a large corpus of tweets sent to the French and Belgian national railway companies by their customers, I have semi-automatically extracted instances of not (very) + adjective (ADJ). Based on previous observations in the literature, I expected positive adjectives to be more frequently used in these negative environments compared to negative ones. As recent research demonstrates that one’s desire to save the interlocutor’s face is not necessarily the only reason why positive adjectives are used in linguistically negative environments, other motivations will also be considered. More precisely, I suggest that in a context where negativity is prevalent, customers using negated positive adjectives kill two birds with one stone: not only do they signal an issue with a product or a service, pointing to expectations that have not been met by the company, but they also mitigate the impact of their negative comments to the positive face of the service managers with whom they are interacting. By offering a quantitative, corpus-based analysis of negative constructions, complemented by a qualitative linguistic analysis of selected examples, this research sheds new light on users’ lexical choices in online negative customer feedback. Full article

Optimizing travel routes in urban transportation networks is essential for enhancing traffic efficiency in major cities. This study focuses on optimizing the combined subway and taxi travel routes from Beijing Union University to Beijing South Railway Station, a critical route for students and staff in Beijing. To address this, we propose three genetic algorithms: the Standard Genetic Algorithm (SGA), the Multipoint Crossover and Elitist Selection Genetic Algorithm (MPEGA), and the Improved Dynamic Crossover and Mutation Rate Genetic Algorithm (IDCMGA). Experimental results indicate that MPEGA reduces the mean travel cost by 15.21%, the variance by 81.72%, and the standard deviation by 57.25% compared to SGA. Additionally, IDCMGA reduces the average by 1.76%, the variance by 63.16%, and the standard deviation by 39.30% compared to MPEGA. The improved IDCMGA algorithm demonstrates significant advantages over the other two algorithms in terms of global optimization capability, convergence speed, and stability, and is more adept at adapting to new traffic conditions to identify the optimal route. Optimizing this route not only reduces commuting time and costs but also alleviates traffic congestion, thereby enhancing the overall efficiency of the urban transportation system. Full article

Due to the capability of multiplexing thousands of sensors on a single optical cable, ultra-weak fiber Bragg grating (UWFBG) vibration sensing technology has been utilized in monitoring the vibration response of large-scale infrastructures, particularly urban railway tracks, and the volume of the collected monitoring data can be huge with the great number of sensors. Even though the train-induced vibration responses of urban railway tracks constitute the most informative and crucial component, they comprised less than 7% of the total operational period. This is mainly attributed to the temporal sparsity of commuting trains. Consequently, the majority of the stored data consisted of low-informative environmental noise and interference excitation data, leading to an inefficient structural health monitoring (SHM) system. To address this issue, this paper introduced an adaptive monitoring strategy for railway track structures, which is capable of identifying train-load patterns by leveraging deep learning techniques. Inspired by image semantic segmentation, a U-net model with one-dimensional convolution layers (U-net-1D) was developed for the pointwise classification of vibration monitoring data. The proposed model was trained and validated using a dataset obtained from an actual urban railway track in China. Results indicated that the proposed method outperforms the traditional dual-threshold method, achieving an Intersection over Union (IoU) of 94.27% on the segmentation task of the test dataset. Full article

In 2016, Carlos Moreno proposed the concept of “15-minute cities” based on the principles of proximity, diversity, density, and ubiquity. In fact, he re-formulated (“re-invented”) some of the already existing planning principles, making them recognized and desired by non-professionals. Moreno, however, paid little attention to the external connectivity of neighborhoods, assuming that most needs would be satisfied locally. This paper aims to discuss the concept of “15-minute cities” from the transport planning point of view and investigate how the concept can contribute to such planning. The research review conducted in this paper suggests that similar actions in the past caused a modal shift from the use of cars to public transport, rather than a radical limitation of total transport needs. To simplify, if a neighborhood is well designed, people are more likely to walk, ride a bike, and use public transport, but the majority will still commute outside of the neighborhood for work. In the metropolis of the ideal “15-minute city”, Barcelona, the majority of the inhabitants travel to work either by car or public transport, which proves that they need to move outside the neighborhood. This leads us to the conclusions that (1) “15-minute cities” should incorporate the transit-oriented development concept and include public transport nodes, such as railways or underground stations, as the central point of walkable, multifunctional neighborhoods, and (2) railway/underground station planners should pay more attention to the creation of a proper mix of services at and around the stations according to “15-minute cities” principles. In the future, there should also be more emphasis on re-allocating workplaces to neighborhoods, as well as on researching the actual impact of the (improved and current) “15-minute cities” design on transport volumes. Full article

The majority of rail vehicles worldwide use diesel as a primary fuel source. Diesel engine carbon emissions harm the environment and human health. Although railway electrification can reduce emissions, it is not always the most economical option, especially on routes with low vehicle demand. As a result, interest in hydrogen-powered trains as a way to reduce greenhouse gas (GHG) emissions has steadily grown in recent years. In this paper, we discuss advancements made in hydrogen-powered freight and commuter trains, as well as the technology used in some aspects of hydrogen-powered vehicles. It was observed that hydrogen-powered trains are already in use in Europe and Asia, unlike most developing countries in Africa. Commuter trains have received most of the research and development (R&D) attention, but interest in hydrogen-powered freight trains has recently picked up momentum. Despite the availability and use of gray and blue hydrogen, green hydrogen is still the preferred fuel for decarbonizing the rail transport sector. Full article

Mobility plays a critical role in promoting rural development. However, the current knowledge regarding the factors that influence mobility between rural towns is limited. The objective of this study is to explore the impact of administrative division and regional accessibility on rural mobility to inform development policies and strategies. The administrative division is demarcated by district and city boundaries, and regional accessibility is assessed using various modes of transportation, including cars, high-speed railways (HSRs), and intercity commuter railways (ICRs). A flow-based geographically weighted regression (FGWR) method is employed based on mobile phone signaling data to quantify the associations and identify the local effects of these factors in the Pearl River Delta (PRD). The findings suggest that both administrative division and regional accessibility significantly influence rural mobility. Specifically, the effects of district boundaries on commuting mobility are more pronounced in the central areas along the Pearl River, while the effects of city boundaries on non-commuting mobility between the core area and surrounding regions are more significant. With regard to regional accessibility, cars are the preferred mode of transportation for connections between the core areas of cities along the Pearl River, whereas HSR is favored more for non-commuting trips between the northwest and center regions. This study provides novel empirical insights into the understanding of rural mobility and has significant implications for promoting regional integration. Full article