Search Results (16)

High-speed rail (HSR) station areas play a vital role in shaping urban form, stimulating economic activity, and enhancing spatial vitality. Understanding the factors that influence this vitality is key to supporting sustainable urban development and transit-oriented planning. This study investigates 66 HSR station areas in 35 Chinese cities by integrating multi-source data—Sina Weibo check-in records, urban support indicators, station attributes, and built environment variables—within a city–node–place analytical framework. Using Multiple Linear Regression (MLR) and Light Gradient Boosting Machine (LightGBM) models, we identify key drivers of spatial vitality, while SHAP analysis reveals nonlinear and interaction effects. The results show that city population size, urbanization level, commercial land use, transit accessibility, and parking facilities significantly enhance station area vitality. However, diminishing returns are observed when commercial land and bus stop densities exceed certain thresholds. The station location index shows a negative correlation with spatial vitality. The analysis of interaction effects highlights strong synergies between urban development and functional configuration, as well as between accessibility and service infrastructure. Different station types exhibit varied spatial patterns and require differentiated strategies. This study offers empirical insights for aligning transport infrastructure and land use planning, supporting the development of vibrant, accessible, and sustainable HSR station areas. Full article

This study examines travel mode choice behavior within the context of Thailand’s emerging high-speed rail (HSR) development. It conducts a comparative assessment of predictive capabilities between the conventional Multinomial Logit (MNL) framework and advanced data-driven methodologies, including gradient boosting algorithms (Extreme Gradient Boosting, Light Gradient Boosting Machine, Categorical Boosting) and neural network architectures (Deep Neural Network, Convolutional Neural Network). The analysis leverages stated preference (SP) data and employs Bayesian optimization in conjunction with a stratified 10-fold cross-validation scheme to ensure model robustness. CatBoost emerges as the top-performing model (area under the curve = 0.9113; accuracy = 0.7557), highlighting travel cost, service frequency, and waiting time as the most influential determinants. These findings underscore the effectiveness of machine learning approaches in capturing complex behavioral patterns, providing empirical evidence to guide high-speed rail policy development in low- and middle-income countries. Practical implications include optimizing fare structures, enhancing service quality, and improving station accessibility to support sustainable adoption. Full article

The construction of high-speed railway (HSR) station areas serves as a crucial catalyst for urban spatial evolution. However, the absence of targeted urban management theories has led to widespread spatial resource waste and post-construction abandonment phenomena in these areas. Existing research predominantly focuses on development strategies for individual construction elements of HSR stations yet lacks comprehensive strategy formulation through coordinated multi-level elements from a sustainable perspective. This study establishes a national database comprising 1018 HSR station area samples across China in 2020, integrating built environment characteristics, HSR network topology, ecological considerations, and socioeconomic indicators. Guided by the land equilibrium utilization theory, we employ the random forest Boruta algorithm to identify critical features, using land supply capacity and development intensity as target variables. Subsequently, K-means++ clustering analysis based on these key variables categorizes the samples into nine distinct clusters. Through normal distribution tests, we establish reference ranges for cluster-specific indicators and propose tailored development strategies across multiple dimensions. This research develops a multimodal feature extraction and evaluation framework specifically designed for the large-scale analysis of HSR station areas. The nine-category strategic recommendations with defined quantitative threshold intervals provide decision-makers with visually intuitive, operationally implementable, and practically significant guidance for spatial planning and resource allocation. Full article

This study investigated the characteristics and functionalities of China’s High-Speed Railway (HSR) network based on Complex Network Theory (CNT) and Graph Convolutional Networks (GCN). First, complex network analysis was applied to provide insights into the network’s fundamental characteristics, such as small-world properties, efficiency, and robustness. Then, this research developed three novel GCN models to identify key nodes, detect community structures, and predict new links. Findings from the complex network analysis revealed that China’s HSR network exhibits a typical small-world property, with a degree distribution that follows a log-normal pattern rather than a power law. The global efficiency indicator suggested that stations are typically connected through direct routes, while the local efficiency indicator showed that the network performs effectively within local areas. The robustness study indicated that the network can quickly lose connectivity if key nodes fail, though it showed an ability initially to self-regulate and has partially restored its structure after disruption. The GCN model for key node identification revealed that the key nodes in the network were predominantly located in economically significant and densely populated cities, positively contributing to the network’s overall efficiency and robustness. The community structures identified by the integrated GCN model highlight the economic and social connections between official urban clusters and the communities. Results from the link prediction model suggest the necessity of improving the long-distance connectivity across regions. Future work will explore the network’s socio-economic dynamics and refine and generalise the GCN models. Full article

In Korea, decisions for high-speed railway (HSR) construction are made based on long-term demand forecasting. A calibration process that simulates current trip patterns is an important step in long-term demand forecasting. However, a trial-and-error approach based on iterative parameter adjustment is used for calibration, resulting in time inefficiency. In addition, the all-or-nothing-based optimal strategy algorithm (OSA) used in HSR trip assignment has limited accuracy because it assigns all trips from a zone with multiple accessible stations to only one station. Therefore, this study aimed to develop a backpropagation-based algorithm to optimize trip assignment probability from a zone to multiple accessible HSR stations. In this algorithm, the difference between the estimated volume calculated from the trip assignment probability and observed volumes was defined as loss, and the trip assignment probability was optimized by repeatedly updating in the direction of the reduced loss. The error rate of the backpropagation-based algorithm was compared with that of the OSA using KTDB data; the backpropagation-based algorithm had lower errors than the OSA for most major HSR stations. It was especially superior when applied to areas with multiple HSR stations, such as the Seoul metropolitan area. This algorithm will improve the accuracy and time efficiency of long-term HSR demand forecasting. Full article

This paper focuses on the role of high-speed rail (HSR) in promoting talent mobility and explores its heterogeneous impact in the employment distribution of local and neighboring regions. This empirical study uses data from 249 prefecture-level cities across the country from 2005 to 2018, combined with geographic spatial vector data. The results show that HSR connection significantly increases local city employment by 5.99%. This result is robust to a series of robustness tests. Heterogeneity results indicate that HSR connection has a significant positive effect on employment in eastern China and large cities, indicating a significant labor inflow from less-developed areas to more-developed areas. Moreover, HSR has a spill-over effect for employment in cities without HSR stations but within a 70 km radius. This spill-over effect is more salient for cities of medium size and in southern China. The mechanism analysis shows that the positive impact of HSR connection on employment mainly stems from the entry of new firms especially those in high-tech industries. This study not only highlights the important role of high-speed rail in promoting labor mobility and employment distribution but also provides strong evidence and insights on how to meet the demand for professionals in closed-loop system innovation and circular economy practices. Full article

The high-speed railway (HSR) has profoundly influenced individuals’ lifestyles and travel behaviors. The development of HSR stations and their surrounding areas plays a critical role in urban growth, enhancing both transport efficiency and urban functionality. This study investigates the development of HSR station areas, with a particular focus on Shanghai Hongqiao station, emphasizing the enhancement of street vitality as essential for integrated urban development. Street vitality in station areas is closely associated with individuals’ activities and travel behaviors, influenced by walking accessibility and the built environment. Understanding these factors is crucial for improving the efficiency and attractiveness of HSR station areas. Although extensive research has examined the separate impacts of the built environment and walking accessibility on street vitality, a significant gap remains in comprehending their synergistic effects. This study employs GPS and point-of-interest (POI) data to analyze the stay time of HSR passengers in station areas. Utilizing machine learning algorithms and geographic information system (GIS) tools, this research models the impact of walking accessibility and the built environment on passengers’ stay time. The results indicate that passengers are more inclined to remain within areas accessible by a 7 min walk from the station. Furthermore, the synergistic effects of walking accessibility and the built environment can inform the spatial planning of various functions. These findings provide valuable insights for urban planners and policymakers aiming to enhance the development and efficiency of HSR station areas. Full article

An environmentally conscious architectural design of a railway station can have a substantial influence on government spending. Nevertheless, an extensive collection of guidelines for using sustainable design principles in the construction of a railway station can provide several advantages. The goal is to review design visions for railway stations in Thailand, as reflected in student theses and government proposals, from 1983 to 2022 for sustainable design aspects in tropical climates. We perform an analysis of architectural design aspects including service areas, shape, entrances, roofing, style, and development in order to uncover design trends and possible areas that may be enhanced. Station designs are mostly characterized by curved and gable roofs, with 3D curved buildings being the next most common feature. High speed rail (HSR) stations stress local cultural elements in their major entrances while also improving passenger flow. Public buildings frequently employ curved or gabled porticos to achieve a majestic look. Although university theses place a high importance on conceptual design and functionality, it is essential to also consider cost-effectiveness. Key design considerations for future railway stations are transparency, connection, efficient mobility, and cost–time efficiency. The research uncovers deficiencies in user-centered design for thermal comfort and inclusiveness (design-for-all) in Thailand’s tropical environment. Addressing these aspects is critical for future sustainable railway station design evaluations. Full article

The purpose of this paper is to compare the differential impact of Taiwan High-speed Railway (T-HSR) and Hainan East Ring High-speed Railway (HER-HSR) stations on the surrounding construction land expansion, reveal the underlying institutional reasons, and then provide policy recommendations for coordinating the rational development of land resources and ecological environment protection around high-speed railway (HSR) stations. The research methods include the Institutional Analysis and Development (IAD) framework, buffer analysis, and GIS spatial analysis. The results show that (1) The spillover impact of HSR stations on the surrounding construction land expansion is the result of the game between different actors around the development and protection of land around HSR stations under the action scenarios of various external factors. The surrounding construction land of 12 stations of T-HSR increased by 269.98 km² within the study scope and period, while the surrounding area of 10 stations in HER-HSR increased by 187.61 km². (2) There are nine stations in T-HSR that affect the expansion of surrounding construction land within 1.0–3.0 km and lead to the expansion of construction land of 22.44 km², while there are six stations in HER-HSR that affect the expansion of construction land within 1.5–3.5 km and lead to the expansion of construction land of 24.20 km². Other stations cannot effectively identify their areas of influence due to other reasons. (3) Each station of HER-HSR has a stronger influence intensity and degree on the expansion of surrounding construction land than that of T-HSR, which is closely related to institutional factors such as land planning, land property rights, and public participation. In conclusion, the differences in land planning, land property rights, public participation, and other basic systems will lead to differences in the expansion of surrounding construction land for HSR stations. This research aims to provide institutional adjustment suggestions to achieve coordinated economic development and ecological protection around HSR stations in two Chinese islands with different institutional environments. Full article

With rapid high-speed railway (HSR) developments in China, HSR-based transit-oriented development (TOD) has proliferated across the country. Although local governments claim that HSR station areas are planned according to TOD principles, some scholars argue that these station areas actually contribute to unsustainable development. This study investigates two main questions: (1) what success factors should be included in a TOD plan for HSR station areas? (2) to what extent are these factors considered in the plans of Chinese HSR station areas? To answer these questions, we use content analysis to compare spatial plans for 15 HSR station areas across China, triangulating the findings via in-depth interviews and field investigations. This study reveals that most of the factors in the plans for HSR station areas deviate from TOD principles, especially in small- and medium-sized cities. We find that Chinese local governments mainly use TODs as a tool to promote suburban expansion around HSR stations. Full article

The development of the HSR station area is the result of the combined effect of the three elements of transport, place, and industry. This study introduces the industrial dimension and constructs the node-place-industry model to empirically analyze the development potential of station areas along the Hunan section of the Beijing–Guangzhou and the Shanghai–Kunming high-speed railway lines. The results show that (1) the development of the three spatial elements of the station area is mostly out of sync, and the node value has the highest fit with the integrated potential value of the station area; (2) there is a significant correlation between the magnitude of the combined potential of the station area and the site location, station class and time of development; (3) according to the results of the cluster analysis, it was found that most of the stations were in a state of disequilibrium, and the main reason was that the functional value of the place did not match with the value of industrial aggregation. In particular, the introduction of the industry dimension extends the NP model and establishes a tessellated analytical framework for station type classification, providing an interesting assessment tool for the sustainable development of transport hub areas. Full article

In this paper, we study the communication performance of applying unmanned aerial vehicles (UAVs) combined with intelligent reflective surfaces (IRS) in a high speed railway (HSR) scenario. This study investigates the design and performance of (multiple-input-multiple-output) MIMO systems with UAV and IRS assistance technology in high-mobility scenarios. Direct links between base stations (BS) and trains are often obstructed in suburban environments, especially in mountainous areas. We mount the IRS on the UAVs so that it can assist in the communication between the trains and the BS. With the help of the UAV-IRS, straight-line links can be established effectively, which greatly improves communication for train passengers. This paper considers the employment of large-scale antenna arrays at both the BS and train ends. Train passengers communicate with UAVs via antennas assembled on the roof of the train as gateways, which in turn communicate with the BS. We consider two types of antenna layouts on the train: all antennas are located in the center of the train named Co-located antennas (CA) layout and uniformly distributed along the train called distributed antennas (DA) layout. We can obtain the analytical up-link capacity by averaging over all locations in a cell for the above two layouts by considering the radio frequency consumption. Overall, the CA layout is found to be a better option for trains when attempting to maximize cell mean value of capacity, and DA layout achieves a more uniformly distribution of capacity over the entire cell. Ultimately, the best solution will depend on the specific requirements and constraints of the selected deployment scenario. Full article

As a new engine of urban development, the high-speed rail (HSR) station area is an emerging location where the service industry is concentrated. This study aims to reflect the development of accommodation facilities in transport hub areas through the spatial distribution and agglomeration characteristics of the lodging industry in HSR station areas. HSR stations in Beijing, Tianjin, Nanjing, Jinan, Kunshan, and Xuzhou are selected. The Geodetector model is applied to analyze the pertinent driving factors. The findings indicate that: (1) The smaller the population size of the city, the closer the high agglomeration area of the accommodation industry in the HSR station area is to the HSR station. (2) The longer the HSR station is open, the stronger the agglomeration intensity of the accommodation industry is. (3) At HSR stations in various cities, the driving factors affecting the accommodation industry are heterogeneous. The interaction between the factors has a synergistic enhancement effect. Full article

The rapid development of high-speed rail (HSR) and station areas has shortened the spatial and temporal distances among cities, improved the accessibility of cities, and affected the spatial agglomeration and diffusion of populations and of social and economic activities. This has led to spatial reconfiguration of production factors within cities, which has the potential to drive the reconstruction of urban spatial structures. Based on POI and land-use data, this paper defines the spatial scope of the HSR station area and explores the characteristics and influencing factors of its spatial structure from the perspective of industry. The study area i is set at 2000 m. Since the opening of the HSR, the industrial distribution has exhibited a significant circular, multi-core, and axial belt spatial structure. The spatial structure of each sub-industry is different. On the whole, internal and external transport and agglomeration economies have significant impacts on the industrial spatial distribution, and land rent has gradually decreased in importance with the development of HSR station areas. The intensity of the effects of different factors varies among different industries. The mechanisms by which the spatial structure of the station area is formed are discussed and include location accessibility, micro-market factors, node station attributes, the availability of a sufficient amount of undeveloped land, the characteristics and needs of HSR passengers, and policies and systems. Full article

Investments in high-speed rail (HSR) development contribute to reducing regional disparities and improving territorial cohesion. When studying the efficacy of HSR investments, the travel time (and effort) spent on getting to and from the HSR station is crucial. In large urban areas there may be more than one station, and a peripheral station may complement the central stations and become a powerful vector for development. The rationale of this paper revolves around the possibility of applying a methodology based on generalised cost (GC) functions to study the advantages of new HSR-related projects in different locations. With this aim, we evaluate a real example in Seville (Spain) to determine whether the improvement in metropolitan accessibility to HSR services justifies the implementation of a new peripheral station, using a methodology to assess the territorial accessibility based on GC functions and modal travel times obtained with GIS methods, followed by an economic assessment based on a cost-benefit analysis. The paper ends with the main conclusions and a discussion of the methodology applied, the reductions in generalised costs resulting from the new station, the relevance of the case study, the limitations of the approach and further research stemming from this study. Full article