Against the backdrop of urban rail transit shifting from large-scale expansion to quality improvement of existing assets, increasing uncertainty in land and property development revenues, and rising long-term operational pressures, the notion that "building rail transit is building the city" has become an urban governance proposition during the transition from intensive rail construction to long-term operation. This paper takes the 30-year development of Shenzhen rail transit as a case study and adopts qualitative interviews based on first-hand materials and case analysis to examine how rail transit is embedded in urban spatial organization and governance processes, thereby being transformed into a form of city-building capacity. Based on the correspondence between different stages of rail transit development and urban transformation in Shenzhen, the study systematically analyzes the functional mechanisms of rail transit in terms of public-interest positioning, network organization, station-area functions, and coordinated implementation, and further examines the operational logic of the "building rail transit is building the city" model. The findings suggest that the urban value of rail transit is not directly derived from network scale or property-led development along rail corridors, but is progressively realized through improved accessibility, spatial restructuring, and interdepartmental coordination; the key to the operation of this model lies in the recirculation of spatial value generated by public investment and benefit-sharing mechanisms, rather than in simple market-oriented development activities. In the context of existing-asset-oriented development, the continued role of rail transit in "building the city" should shift from scale expansion and development-revenue orientation to improving the efficiency of existing networks during the stable operation phase, station-area renewal, and strengthening public service provision.

To bridge the gap between AI technological breakthroughs and industrial value release in urban rail transit and foster new-quality productive forces as well as high-quality sustainable development, this paper studies AI implementation with the technical logic of "perception-decision-making-execution" and the connotation of new-quality productive forces, based on academic literature, patents and industry questionnaire data. It targets practical problems including fragmented AI implementation, lagging factor allocation and insufficient knowledge transformation, and puts forward a holistic AI implementation framework with three core innovations. The study concludes that a high-quality urban rail transit knowledge base is the top priority, data elements are the core of innovative factor allocation, and 1-to-N scenario expansion is the inevitable path for urban rail transit AI to translate technological breakthroughs into industrial value.

With the continued expansion of urban rail transit networks and the increasing complexity of operating scenarios, passenger demand exhibits more complex spatiotemporal patterns, posing higher requirements for train operation organization and passenger flow control. Short-term passenger flow prediction is an important basis for urban rail transit operation management and provides key support for operational decision-making. In recent years, artificial intelligence-based methods have become an important technical approach for improving short-term passenger flow prediction performance, owing to their strong capability to extract complex spatiotemporal features. This review focuses on artificial intelligence-based methods for short-term passenger flow prediction in urban rail transit systems. It first constructs a task analysis framework from five dimensions: prediction scenarios, prediction targets, data sources, prediction methods, and evaluation metrics. Second, the development trajectory of prediction models is systematically reviewed. Furthermore, recent studies and major challenges are summarized for different prediction tasks, including station inflow and outflow passenger flow prediction, origin-destination passenger flow prediction, section passenger flow prediction, multi-type passenger flow collaborative prediction, and multimodal traffic prediction with rail transit as the backbone. Finally, future research directions are discussed from the perspectives of large language models, trustworthy and interpretable prediction, an end-to-end predict-and-optimize learning framework, and world models. This review shows that short-term passenger flow prediction in urban rail transit is evolving from single-flow-type, single-metric, and single-task prediction toward integrated development featuring multi-source perception, multi-type passenger flow collaboration, and multi-metric evaluation. Future research should further emphasize general adaptability, uncertainty awareness, trustworthy risk assessment, decision-oriented prediction, and world-model-driven dynamic deduction, with the aim of building an integrated intelligent prediction and simulation framework for complex operational scenarios and supporting refined operational decision-making in urban rail transit.

To explore in depth the technological evolution logic and independent innovation path of metro in China from combat readiness assistance to modern urban engine transformation. Focusing on five key components: rail and continuously welded rail, fasteners, turnouts, monolithic track bed, and vibration-damping track structures, the technological progress in each area is elaborated: in addition to the adoption of high-speed rail technologies based on project requirements, the characteristics of metro systems—such as numerous small-radius curves and frequent overloading—have also driven the application of wear-resistant rails in locations like sharp curves and turnout sections; fasteners have diversified into a standardized system represented by series such as DT、ZX、WJ, with continuous improvements in design and manufacturing; turnouts have evolved from national railway standards to urban rail series such as Cheng Gui suited to metro engineering needs; the monolithic track bed has established a standard system centered on concrete long-sleeper embedded types, alongside new structural forms such as prefabricated and assembled technologies; and vibration-damping track structures have formed a diversified technical system covering fasteners, sleepers, and track-bed solutions. Looking ahead, track structure technology will continue to advance in design, construction, maintenance, and upgrading of in-service lines, while China's metro technical standards are progressively moving toward internationalization.

In response to the need for a systematic understanding of the development trajectory, market characteristics, and practical challenges of China's overseas urban rail transit infrastructure market, this study focuses on urban rail transit infrastructure projects launched overseas by Chinese enterprises between 2005 and 2025. It conducts a comprehensive statistical analysis of project numbers, host countries, route mileage, construction status, regional distribution, system types, and development stages, and further examines the formation of the overseas urban rail transit market landscape, its evolutionary trajectory, and the major problems faced by Chinese enterprises. On this basis, the study proposes systematic solutions from seven dimensions: regional market positioning, industrial chain extension, risk prevention and control, financing models, cost management, rules and standards, and technological and talent reserves. These solutions include implementing tiered and targeted market strategies based on regional potential, developing a TOD-based "urban rail transit + integrated development along the corridor" overseas ecosystem, establishing a country-specific, tiered geopolitical risk prevention and early-warning system, innovating diversified self-sustaining financing models supported by multilateral finance and station-area property development, building localized benchmark databases and implementing full life-cycle cost control mechanisms, strengthening "soft connectivity" through rules and standards, and enhancing core technologies such as autonomous operation and intelligent maintenance, together with international talent reserves. The results show that from 2005 to 2025, Chinese enterprises constructed 55 urban rail transit lines in 21 countries across five continents, with a total completed and under-construction mileage of 984.2 km. Geographically, the overseas market is highly concentrated in three major regions: Southeast Asia, West Asia and North Africa, and Sub-Saharan Africa. In terms of system type, large-capacity metro systems remain dominant. The development process has gone through three stages: initial exploration, Belt and Road Initiative-driven expansion, and transition toward high-quality development. It also exhibits a shift from civil engineering contracting to full industrial chain output, and from short-term operation and maintenance services to long-term concession-based operation. Meanwhile, Chinese overseas urban rail transit projects still face problems such as delays in project implementation, a significant increase in bidding failures, and losses in some projects. Overall, China's overseas urban rail transit industry is at a critical stage of transition from extensive scale expansion to sustainable value-oriented output. It is therefore necessary to enhance the overall competitiveness and sustainable development capacity of overseas urban rail transit projects through targeted market positioning, integrated development models, proactive risk control, diversified financing mechanisms, full life-cycle cost management, alignment of rules and standards, and the development of core technologies and international talent systems, so as to better support Belt and Road infrastructure connectivity and the building of a global community of shared future in transport cooperation.

With the transition of urban rail transit toward networked operations, the scientific planning of transit networks is critical for ensuring operational efficiency and service quality. This systematically the research progress on optimization models and methodologies for urban rail transit networks, based on relevant studies published from 2015 to 2025. Current rail transit network optimization models suffer from idealized assumptions and insufficient characterization of practical constraints. Moreover, the three mainstream solution approaches—exact algorithms, intelligent heuristic algorithms, and deep reinforcement learning—each have respective drawbacks in computation efficiency, stability, generalization capacity and other aspects. The paper begins by establishing a taxonomy of transit network planning problems from three perspectives: planning scenarios, modeling formulations, and solution method. Then, in terms of optimization models, the evolution from single-objective to multi-objective formulations is reviewed, highlighting the development of multi-dimensional objective systems involving efficiency, cost, equity, and resilience. This paper further summarizes the main advances in initial network generation models and existing network expansion optimization models. On the algorithmic side, the paper covers exact methods, metaheuristic algorithms, surrogate-assisted optimization, and the emerging deep reinforcement learning (DRL) paradigm, with particular attention to studies that formulate network design as a Markov Decision Process (MDP). It is concluded that the existing optimization models generally have structural defects and deviate from engineering practice. They fail to fully characterize practical constraints such as transfer layouts, capacity limits and time-varying passenger flows, which greatly reduces their practical application value. Five research directions are therefore proposed to improve relevant research: constructing a hybrid optimization framework for large-scale networks, establishing an integrated supply-demand coordination model, developing collaborative optimization theories for multi-mode rail transit systems, forming a low-carbon sustainable optimization system, and building a digital twin-driven dynamic decision-making model.

To address the limitation of the traditional Node-Place model in capturing actual passenger-flow vitality and its variation across travel scenarios, this study introduces a vitality dimension and develops a Node-lace-vitality model to identify urban rail transit station-area types and examine their differences across travel scenarios. Taking 211 urban rail transit stations in Xi'an as the sample, this study integrates multi-source data, including rail transit network topology, station facilities, feeder transport services, built environment characteristics, population activities, point of interest (POI) functional facilities, and hourly origin-destination (OD) ridership. An evaluation indicator system covering the three dimensions of node, place, and vitality is established. A combined weighting method is used to determine indicator weights, and a Gaussian mixture model is applied to identify station-area types under workday and National Day holiday scenarios. The transition characteristics of station-area types across different scenarios are then analyzed. The results show that the node, place, and vitality scores of Xi'an rail transit stations generally exhibit a spatial pattern of "high values in the central urban area and low values along peripheral lines". Under the National Day holiday scenario, some stations show a significant increase in passenger flow vitality. The station areas can be classified into five types: hub-integrated stations, station-city coordinated stations, vitality-responsive stations, place-supporting stations, and basic-cultivation stations. Their spatial distribution presents a clear concentric pattern characterized by "central agglomeration and peripheral differentiation". Station-area types remain generally stable between workday and holiday scenarios. Among the 211 stations, 192 stations retain the same type, accounting for 91.00%, while 19 stations experience type transitions, accounting for 9.00%. These transitions mainly occur between place-supporting stations and basic-cultivation stations, and are primarily distributed outside the Second Ring Road. The findings provide a scientific basis for station-area functional optimization, peripheral station cultivation, differentiated development under the Transit-Oriented Development (TOD) framework, and refined rail transit operations management.

There are significant differences in passenger flow distribution patterns between metropolitan rapid rail transit and metro systems. How to conduct a scientific and reasonable evaluation is crucial to the healthy development of metropolitan areas and urban agglomerations in China, and thus deserves in-depth exploration. This paper systematically defines the connotation, calculation methods, and applicable boundaries of passenger transport intensity and passenger flow density based on the Urban rail transit operation indicator system (GB/T38374—2019) and the 2025 annual statistical data of the China Urban Rail Transit Association. It compares and analyzes the differences between metropolitan rapid rail transit and metro in terms of travel space, time, demand, and operational characteristics. Using data from 34 operational metropolitan rapid rail transit in 22 cities across the country and typical lines in multiple cities as examples, this paper conducts a quantitative empirical analysis. The results show that in 2025, the average passenger transport intensity of medium-capacity system category including metropolitan rapid rail transit in China was only 1.8 thousand person-times/km·day, far lower than the 7.3 thousand person-times/km·day for metro systems, while the passenger flow density reached 24.6 thousand person·km/km·day, indicating that its transport efficiency was underestimated. The average travel distance of metropolitan rapid rail transit is generally greater than 30 km, which is the core factor causing the evaluation deviation between the two indicators. Passenger flow density is more capable of matching the functional positioning of long-distance transportation of metropolitan rapid rail transit. The passenger flow density indicator is also applicable to metro lines with shorter travel distances in central urban areas, but due to the relatively short average travel distance of metro, passenger transport intensity and passenger flow density are highly positively correlated. Building on a systematic review of existing studies, this paper proposes a multi-dimensional evaluation framework for metropolitan rapid rail transit, with passenger flow density as its core while incorporating average travel distance and spatiotemporal convergence benefits. The objectivity of the proposed framework is validated through theoretical analysis, empirical testing, and comprehensive benefit assessment. Optimization recommendations are further offered to provide theoretical support and reference for the planning approval, operational assessment, and high-quality sustainable development of metropolitan rail transit.

To review the research progress of Virtual Coupling (VC) technology in rail transit transportation organization and identify its applications in train operation plan optimization and rescheduling, this paper presents a comprehensive literature review of recent studies in the field. From an operational and service-oriented perspective, 42 representative publications published between 2022 and 2025 were collected from major academic databases, including Web of Science, Scopus, IEEE Xplore, and CNKI. Research on train operation plan design, timetable optimization, integrated timetable and rolling stock circulation planning, as well as train delay rescheduling, disruption management during disruption and recovery phases, was reviewed and compared. The results indicate that VC technology can significantly enhance line capacity and operational flexibility through reduced train headways and dynamic coupling and decoupling operations. In terms of operation planning, existing studies have evolved from isolated timetable optimization to integrated optimization of timetables, stopping patterns, train routing, and rolling stock circulation. In terms of operation rescheduling, VC has demonstrated considerable potential in improving transportation organization resilience and passenger evacuation efficiency under disruption scenarios. However, current research still faces several limitations, including insufficient integration among planning elements, limited consideration of complex rail networks, inadequate investigation of multi-strategy collaborative rescheduling, and a lack of unified frameworks covering the entire disruption process. Future research should focus on integrated optimization of timetables, stopping patterns, train routing, and rolling stock circulation; integrated modeling of train operation organization, dispatching, and control; multi-strategy collaborative rescheduling; full-process disruption rescheduling; and the application of intelligent optimization approaches such as deep reinforcement learning in VC-enabled rail transit systems.

To improve the operational safety of urban rail transit trains, mitigate train operation risks under extreme weather conditions, and address the significant performance decline of traditional wheel-rail adhesion-based braking methods, this paper investigates the vibration generation mechanism and dynamic response characteristics of high-suspension magnetic track brakes under emergency braking conditions. Based on its working principle of electromagnetic adhesion and friction braking, the vibration characteristics are identified by simulating the effects of rainy and snowy weather on the track. The vibration transmission path consisting of the braking device, bogie, and car body is established. Vertical and lateral vibration data under various working conditions are collected via triaxial acceleration sensors, and a quantitative evaluation of vehicle running safety and ride comfort is conducted based on ride smoothness and stability indices. The results show that under wet track conditions in rainy and snowy weather, the peak vibration acceleration of the high-suspension magnetic track brake is less than 2.5 m/s². Vibration is transmitted through the bogie-car body path and exerts a minor impact on the service life of on-board electronic equipment. The braking mode of the high-suspension magnetic track brake has little effect on vehicle ride smoothness. Adding magnetic track brakes is of great engineering value for ensuring the high-speed, safe, and comfortable operation of urban rail transit under diverse complex meteorological conditions.