The year 2025 marks the concluding year of the 14th Five-Year Plan period. By the end of this period, 58 cities across 28 provincial-level administrative regions in Chinese mainland have opened urban rail transit systems, with 382 operating lines totaling 13,071.58 km in length, of which subway lines account for 10,007.06 km, representing 76.56% of the total. By the statistical period, 1,976.41 kilometers of fully automated operating lines had been opened, accounting for 15.12% of the total operating length. In 2025 alone, 55 new urban rail transit operating lines (segments) were added, with a total new operational length of 910.80 kilometers. This includes 700.97 kilometers of new subway lines and 491.99 kilometers of new fully automated operating lines. It is projected that approximately 4,000 kilometers of new urban rail transit operating lines will be added during the 15th Five-Year Plan period, bringing the total operating length in Chinese mainland to around 17,000 kilometers by the end of this period.

Most existing studies have overlooked the impact of rail transit integration at the metropolitan scale on accessibility to tertiary hospitals and its spatial equity. To address this gap, this study uses the two-step floating catchment area (2SFCA) model and the adjusted mean absolute deviation to measure accessibility to tertiary hospitals and its spatial equity, sets two scenarios (the status quo and the rail transit integration scenario), and evaluates the impact of rail transit integration on accessibility to tertiary hospitals and its spatial equity in the Chengdu Metropolitan Area. The results show that rail transit integration has substantially improved accessibility to tertiary hospitals. As rail transit integration progresses, spatial polarization in accessibility has gradually weakened, and the number of high-accessibility areas has declined. However, the accessibility gap between the eastern and western sides of the Longquan Mountains has become increasingly pronounced. Rail transit integration has reduced spatial disparities in accessibility to tertiary hospitals and fostered spatial equity. These findings provide valuable insights for the rational allocation of high-quality medical and rail transit resources.

Addressing the lack of systematic review in existing literature on the theoretical aspects of four-network integration, particularly its connotation of four-network integration, this study first proposes that the connotation of four-network integration mainly includes multi-level rail transit classification and multi-level rail transit integration, which complement each other. The deep requirement of multi-level rail transit classification is to ensure efficient coordination of the "four networks," with a hierarchical structure that facilitates the balanced development of passenger flow. The focus of multi-level rail transit integration development can be subdivided according to the implementation path into planning and construction integration, operational service integration, and management mechanism integration, ultimately achieving temporal, spatial, and functional integration. Secondly, based on the connotation, this paper analyzes two domestic cases: the cross-platform interchange at Chengdu's Xipu Station and the cross-line operation between Chongqing Rail Transit Jiangtiao Line and Metro Line 5. Thirdly, it examines the challenges currently faced in promoting four-network integration in China, specifically including unreasonable network structure allocation, lagging planning and construction coordination, insufficient coordinated service levels, and deficient coordinated institutional mechanisms. Finally, targeted strategic recommendations are proposed in four aspects: rail transit service demarcation for the "four networks," planning and construction integration, operational service integration, and management mechanism integration, aiming to provide theoretical support and practical guidance for the sustainable and healthy development of four-network integration in China's rail transit.

In view of the difficulties in emergency evacuation caused by the increasing complexity of underground spaces in subway stations, and based on an extensive review of domestic and international literature, this paper first analyzes the evacuation characteristics and common features of different types of underground spaces, It examines evacuation scenarios, pedestrian behavior, and evacuation analysis methods in disaster contexts, and summarizes the evacuation behavior traits across station types. Secondly, the study delves into recent advancements in evacuation experiments and simulation technologies, covering physical and simulated experiments, including core algorithms, simulation processes, and inherent limitations of mainstream simulation platforms. It also highlights the impact of spatial features on simulation experiments and identifies current research hotspots. Finally, focusing on layout and path optimization for evacuation, the paper explores related methodologies and practical applications. On this basis, it points out that existing research is predominantly centered on theoretical modeling and quantitative analysis, with a lack of field validation that limits practical effectiveness. There is also a deficiency in interdisciplinary integration, especially concerning psychological and social dynamics of crowd behavior, which constrains the effectiveness of evacuation strategies in emergency practice. Therefore, the study suggests enhancing model realism through virtual reality, big data, and artificial intelligence technologies to improve simulation accuracy; and encourages interdisciplinary collaboration among psychology, sociology, urban planning, and safety engineering to comprehensively analyze crowd evacuation behaviors in different types of underground spaces in subway stations during emergencies, thereby providing a solid theoretical foundation and practical reference for future research.

To overcome the limitations of the standalone architecture of traditional smart stations and promote the transformation of urban rail transit toward networked and intensive operation, this paper proposes and verifies a cloud-based deployment paradigm for intelligent switching stations utilizing a line-level cloud platform. First, guided by the Development outline for smart urban rail transit in China, a hierarchical and decoupled construction framework for intelligent switching stations is established, focusing on the flexibility and scalability of the system architecture. Taking Changsha Metro Line 6 as a case study, this paper elaborates on the implementation of cross-service collaboration and data model sharing among stations by leveraging the line-level urban rail transit cloud platform, including the design of data transmission protocols, the construction of platform architecture, and the optimization scheme of information flow. The deployment of the cloud platform has successfully connected the service data links of all stations along the line, enabling centralized monitoring and intelligent dispatching. Practical results show that this paradigm significantly improves the utilization efficiency of hardware resources, reduces operational costs and labor input, and optimizes the business processes of switching stations, cutting the operation time by approximately 80%. Meanwhile, the system effectively reduces the staffing requirement by 3-4 members. This study provides a replicable and scalable cloud migration path for the digital transformation of the rail transit industry. The infrastructure based on the line-level cloud platform can support the core capabilities of intelligent switching stations, realizing an integrated closed loop from "platform construction" to "operational deployment".

Addressing the challenges of surging urban logistics demand, low efficiency of road freight, and environmental concerns, this study analyzes typical cases and summarizes three urban rail freight modes: incidental transport, mixed passenger-freight operations, and dedicated freight trains. It identifies key challenges in operational coordination, facility compatibility, demand matching, and safety management. To resolve these, we propose a "peak-valley" spatiotemporal resource allocation mechanism, flexible facility retrofitting, intelligent scheduling with standardized loading units, and an enhanced safety management system. Furthermore, three tailored operational schemes are designed: an off-peak dynamic incidental transport mode for small parcels, a flexible mixed mode for hub-to-hub batch transport, and a nighttime dedicated freight corridor mode for bulk cargo. This research offers theoretical and practical insights for improving logistics efficiency, reducing traffic congestion, and supporting carbon reduction goals.

To address the issue of urban rail transit network operations being disconnected from local urban development (the "two-skin" problem), this study analyzes the collaborative development characteristics of the "node-place" model in Beijing's rail transit stations. The goal is to provide a decision-making basis for station- city integration. Based on the node-place model theoretical framework, this study adopts multi-source big data analysis methods to construct an evaluation system that incorporates transportation functions (node value) and urban functions (place value). This study takes Beijing's rail transit stations at the end of 2023 as the research objects, divides them into four types of development through spatial clustering, and compares them longitudinally with 2019 data to form five types of evolution trend patterns. The results indicate that the overall development characteristics of the city's stations show a balance between node and place values, with node values slightly higher than place values. Therefore, station-city integrated development should be strengthened at the city level. The 29 stations located on the suburban lines show a continuous trend of deteriorating place value, which is closely related to the lagging land development around the stations. Therefore, it is necessary to strengthen guidance and promote land development around such stations. The research results will help form an improvement project library for different site development issues, providing support for achieving station-city integration. Subsequent research will expand the dimensions of dynamic monitoring and deepen the analysis of the interaction mechanism between rail transit and urban space.

In response to the growing complexity of passenger flow organization and the unclear decision-making mechanism of passengers' path selection behavior during the peak period of urban rail transit stations, this paper collected data through RP (revealed preference) and SP (stated preference) surveys. It constructed an ordered Logit regression model to analyze factors influencing passengers' trust in guidance information, and identified key influencing factors of passengers' path selection behavior based on the mixed Logit regression model. The results show that passengers' gender, age, and preference for guidance information have significant effects on their trust; the recommendation strength of guidance information and the herd effect of group choice behavior have positive effects on passengers' path decision-making. This study provides a new perspective for understanding the information processing mechanism and behavioral decision-making mode of passengers in complex transit environment. The findings provide a theoretical basis for optimizing the efficiency of passenger flow organization in rail transit transfer stations.

Predicting and controlling the surface settlement induced by shield tunneling is a critical engineering issue in underground space development. With the development of artificial intelligence technology, machine learning algorithms have demonstrated significant effectiveness in surface settlement prediction and control. We summarize the theory of machine learning, focusing on four key aspects: database construction, data preprocessing, model selection and evaluation, and shield tunneling parameter optimization under settlement control. Additionally, it critically examines the limitations of existing research in this domain. Current research often neglects the additional impacts of surface structure loads, traffic flow, and pedestrian activities, lacks model interpretability, and struggles to balance prediction accuracy with practical applicability. Future research should focus on developing a comprehensive measurement and evaluation system that incorporates the dynamic effects of surface buildings, traffic, and ground surcharge into settlement prediction models. Furthermore, future work should enhance model interpretability and promote the dynamic updating of machine learning models with real-time monitoring data, thereby providing more scientifically sound guidance for safety control in shield tunneling construction.

To address the lack of a well-established design framework for reducing groundwater level rise caused by metro station construction through diversion measures, this study combines theoretical analysis and physical model tests to investigate groundwater flow rate calculation in karst areas, determination of diversion design parameters, and the relationships of groundwater rise with hydraulic gradient and with diversion area ratio. A site case study is incorporated, and numerical simulation was used to verify the effectiveness of the diversion design scheme. Results show that: after metro station construction, the groundwater flow path lengthens due to station obstruction, causing a rise in groundwater; after implementing diversion measures, the flow path shortens and the rise dissipates; the groundwater rise exhibits a linear correlation with hydraulic gradient, increasing correspondingly with higher hydraulic gradients; under constant permeability coefficient and hydraulic gradient conditions, groundwater rise decreases exponentially with the proportion of diversion channel area, with a critical threshold occurring at approximately 20% proportion, leading to the recommendation that the optimization coefficient for diversion design parameters should be no less than 0.2; both gravel replacement diversion schemes and culvert diversion schemes can essentially restore the elevated hydraulic head to its original state. Numerical simulation results verify the correctness of diversion design parameter values, confirming that the parameter determination method is feasible and meets the requirements for reducing groundwater level rise.