Considering the drawbacks of inconsistent building information modeling (BIM) methods and nonstandard information in rail transit engineering, it is difficult to effectively and uniformly use BIM model data. Therefore, the Industry Foundation Classes (IFC)based BIM component standard library for rail transit engineering was studied. First, the component types, IFC expression of component information, and IFCbased extensibility mechanisms were studied according to the expression requirements of rail transit engineering components. Second, the technology framework of the BIM component standard library for rail transit engineering was proposed, including basic, technical, application, and user layers. Third, the classification and code method in the national standard was used to define the classification and code of these BIM components, and a component information template was proposed to define the component properties and their resource links. Finally, encryption and decryption methods for the BIM component model were applied to ensure the security of the BIM model data. The results showed that the proposed unified BIM component library enabled project participants to use standardized BIM component models to create a project model for rail transit engineering, ensuring the standardization of BIM models.

To address uncertainties in future operational carbon emissions and carbon reduction targets for urban rail transit networks, this study analyzes operational energy consumption data for the Xi'an urban rail transit system from 2018 to 2022. The carbon emission factor method is employed to calculate operational carbon emissions for the past five years. The index method is then used to predict energy consumption and carbon emissions for the next five years. Based on the binding energy intensity requirements outlined in China's Action Plan for Green Urban Rail Development, we quantitatively analyze the total energy saving target for Xi'an's urban rail transit operations over the next five years. Subsequently, the total carbon emission constraint and carbon reduction target are determined. The research results indicate that approximately 175.9×10⁴ tCO2e of total carbon emissions were generated during the operation of the Xi'an urban rail transit system from 2018 to 2022. Under these conditions, it is expected that approximately 321.6×10⁴ tCO2e of total carbon emissions will be generated over the next five years of operations, with traction and station power consumption being the main sources of carbon emissions. If the comprehensive energy intensity reduction target proposed by the association is achieved, compared with the predicted carbon emissions, the carbon emissions of the entire network are expected to reduce by approximately 13% by 2025; the carbon emissions of the entire network are expected to reduce by approximately 15% by 2027; and in total, carbon emissions are expected to reduce by approximately 10% over the next five years.

Subway traction energy consumption can be reduced by optimizing subway timetables. To solve the problem of the impact of passenger flow fluctuations and train delays on the actual energysaving rate, this study proposes a Dueling Deep Q Network (DQN) deep reinforcement learning timetable optimization algorithm combined with a realtime subway power supply current flow calculation model. An interval iterative optimization model based on the spatiotemporal distribution of the dynamic passenger flow was established to suppress the impact of passenger flow variation. The Adaptive Moment Estimation (Adam) and root mean square propagation (RMSProp) methods were applied to predict the Qnetwork and target Qnetwork as well as improve the convergence speed of the model. While minimizing passenger transfer, waiting, and total travel times, this model allows for the seamless switching of energysaving timetables. The test results for Suzhou Line 4 demonstrate the effectiveness of the proposed method. Under the conditions that the arrival time deviation at transfer stations was less than 2 s and the overall operating time of trains remained unchanged, the traction energy saving was 5.27%, and the train kilometer energy consumption decreased by 4.99%.

The operating mileage and total energy consumption of urban rail transit systems are constantly increasing. To accurately calculate energy consumption, the actual trainside energy consumption formula that considers dynamic motor efficiency and an energy consumption simulation and calculation model based on the singleand multiplemasspoint models of train operation are constructed in this study. First, the energy flow process of the train traction drive system was studied, and the relationship between the efficiency of each component and the train operation state was established. Second, the actual train energy consumption calculation based on electric power was deduced according to the twotable method by combining the efficiency conversion of each component. The factors affecting energy consumption were comprehensively analyzed, and an energy consumption simulation and calculation method considering singleand multimasspoint train models was proposed. Finally, taking the four stations and three intervals of a regional line in China as an example, the results show that the operation energy consumption under either the singleor the multiplemasspoint train operation model achieves a deviation of less than 5% compared with the actual energy consumption, which verifies the accuracy of the proposed energy consumption model. In addition, the operational energy consumption of the multimass model was further reduced by a 1.66% deviation from that of the singlemass model. The proposed model provides theoretical support for the optimization of train energy savings and actively contributes to the development strategy of China's green economy.

In the rapid development phase of urban rail transit, issues such as inadequate emergency response and insufficient emergency handling in unexpected events are addressed. This study presents the design of a digital intelligencebased subway safety and emergency assurance system. The design architecture, application scenarios, functionalities, and key technologies of the system are elaborated. This system integrates diverse sources of data, including hydrological, meteorological, and sensor data, and utilizes emerging technologies, such as digital twins, GIS, and BIM. This system manages the entire emergency process of subway operations, including daily safety monitoring, emergency resource management, emergency plan administration, commands, and dispatch. Moreover, it focuses on enhancing capabilities for dealing with three major emergency scenarios: fires, flood prevention, and high passenger flow. This comprehensive development significantly enhances accident prevention, emergency response, and handling efficiency while elevating the levels of digitization and intelligence in the existing emergency management system.

The rail transit Passenger Information System (PIS) utilizes communication and multimedia technology and provides passengers with allround and multiscene information service systems based on a variety of display terminals. To address the drawbacks of the current rail transit Passenger Information System, such as overinvestment in hardware, low deployment and debugging efficiency, long broadcast control transmission link, and poor reliability, this paper proposes a cloud broadcast control technology architecture for the new generation Passenger Information System, which is "system into the cloud and broadcast control into the screen, " and describes in detail the technical advantages brought by the cloud playcontrol architecture through reforming the traditional audio and video transmission modes. The problem regarding picture synchronization on a multidisplay terminal was analyzed. The results show that the cloud playcontrol technology reduces the fault nodes by 50%, improves the deployment and debugging efficiency, achieves intensive construction, and can provide application support for various personalized scenarios f throughout the entire process of passenger travel from arrival to departure, which can provide reference for the subsequent construction of passenger information systems.

Given that the departure capacity of depots has gradually hindered the improvement of the operation level of the main line during morning peak hours, some cities have begun to explore the construction of ATC depots. However, existing calculation methods for vehicle sending and receiving capacity cannot be applied to ATC depots. The throat area capacity calculation method of ATC depots is investigated to compensate for the above shortcomings. First, under the ATC lightsoff mode, the minimum total train departure time is obtained by comparing the total train departure times under different train departure sequences. Second, the maximum throat area passing capacity of the ATC depot is calculated. Finally, using the Guangzhou Luogang depot as a case study, a validation study of the effectiveness of the calculation model of the throat area passing capacity under the ATC lightsoff mode is carried out. The results show that the passing capacities of the throat area under the ATC lightsoff, ATC lighting, train adjustment combination, and train approach modes are 28, 17, 13, and 11 trains/h, respectively; the ATC lightsoff mode has a greater capacity than the other three modes and can better meet the operational demand of the mainline during morning peak hours. The results of this study can serve as a reference for evaluating depot design schemes.

This study investigates the reasonable setting of suburban railway curve superelevations in the case of related specifications and standards that are not unified. The principle of prioritizing the allowable values of each superelevation is not clear. By comparing and analyzing the requirements for curve superelevation settings in different codes and by analyzing examples, this paper proposes the maximum and minimum values of design superelevation, the general allowable values for undersuperelevation, oversuperelevation, and difficult situations, and the allowable values for the superelevation slope ratio, taking into account the Code for Design of Railway Track, Code for Design of Suburban Railway, and other industry standards. The priority of design principles of allowable values for different superelevations is obtained, providing guidance for the setting of curve superelevations for new suburban railways and providing a reference for the improvement of industryrelated standards.

Synthetic sleepers of fiberreinforced polyurethane foam were initially applied in urban railway traffic to adapt to the linear induction motor system, and they have been developed into national and heavyhaul railways in recent years. Synthetic sleepers have been widely researched and applied nationwide owing to their excellent overall performance. The technological development history and standards of synthetic sleepers in China were analyzed and compared with foreign and ISO standards. In addition, the application progress, application problems, and solutions were investigated. Suggestions for the development and prospects of polyurethane synthetic sleepers in China were proposed by combining the requirements of domestic rail traffic with the application problems of synthetic sleepers.

The complexity of deepexcavation construction arises from the influence of various potential risk factors on the construction procedure. To address this issue, this study introduces an intuitionistic fuzzy TOPSIS method aimed at identifying potential highrisk factors. Initially, potential risk factors were determined through an analysis of the failure modes derived from prior excavation accidents, insights from practical engineering projects, and the expertise of engineering professionals. Subsequently, a risk evaluation hierarchy was established, and weights were assigned to experts and criteria using intuitionistic fuzzy numbers. A practical project involving a deep excavation was conducted to validate the feasibility of the proposed method. The results indicate that the TOPSIS method effectively identified highrisk factors. The developed method serves as a valuable decisionmaking tool for the safety risk analysis and control of excavation construction in similar engineering projects.