In response to the maintenance needs of bridge bearing defects, existing bearing replacement methods all require jacking up the bridge to complete the bearing replacement, significantly impacting bridge structural safety and traffic operations. This study designs and manufactures a “lowmeltingpoint alloy bidirectional heightadjustable forcemeasuring bridge bearing, leveraging its bidirectional heightadjustable characteristics to develop a technology for replacing bridge bearings without jacking up the bridge. Against the backdrop of practical engineering applications, a comparison is made between the "bridge bearing replacement technology without jacking up the beams” and the existing “bridge bearing replacement technology with jacking up the beams." Utilizing this technology, bridge bearing replacement can be achieved without jacking up the superstructure, effectively avoiding stress changes in the bridge structure caused by jacking and enhancing maintenance efficiency and safety. Additionally, this technology is easy to operate, has minimal impact on traffic operations, and possesses broad applicability and promotional value.

Data plays a crucial role in the successful deployment of urban rail transit large language models (LLMs). RetrievalAugmented Generation (RAG) technology emerges as a promising approach for developing industryspecific LLMs and mitigating hallucination issues. However, the lack of comprehensive industry knowledge bases hinders its effectiveness. This study proposes a novel framework for constructing a knowledge graphbased RAG knowledge base for urban rail transit LLMs. This framework consists of four key dimensions: classification skeleton, semantic benchmark, feature rules, and logical relationships. These dimensions are implemented through entity classification systems, terminology dictionaries, attribute libraries, and entity relationship tables, respectively. By incorporating industryspecific attributes for entities, this approach goes beyond the traditional subjectpredicateobject triple structure of knowledge graphs, resulting in a comprehensive and multifaceted representation of industry knowledge. This knowledge base serves as the core component of the RAG system, providing standardized, reliable, and traceable domain knowledge through a systematic pipeline of data collection, structuring, vectorization, and knowledge representation. This process significantly enhances the reliability and domain expertise of the content generated by urban rail transit LLMs, paving the way for a new era driven by both data and knowledge.

Guided by the need to address the shortcomings of subjective selection and the mismatch between capacity and demand in the selection of existing medium and low capacity urban rail transit standards, the standardized and procedural decisionmaking system for standard selection is developed. Firstly, the 4 criterion and 16 index evaluation system is established, considering constraints such as peak hour passenger flow, minimum transport capacity reserve, and the number of train operations. A multiobjective optimization model is constructed to determine the set of candidate rail transit systems. Besides, the CRITICTOPSIS algorithm is constructed to determine the weight coefficient values of each indicator and the optimal solution distance, thereby determining the optimal track system. Finally, using the Sline as the background for example verification, 5 alternative track systems are evaluated through a quantitative model. The CRITIC and TOPSIS algorithms were implemented using Python software. The decision values of rail transportation system rank in the order of selfguided monorail, crossseat monorail, light rail, guideway rubber wheel and low and mediumspeed magnetic levitation, indicating that the optimal rail system for line S is the selfguided monorail. Analyzing the standardized scoring matrix and index weight values of each type of rail system, the research results show that the model and algorithm proposed in this paper can effectively solve the problem of low and mediumcapacity rail transportation system selection.

The Virtual track train (VTT) has been put into commercial operation as a new type of urban rail transport in China in recent years. To further understand VTT's operational performance, it is essential to develop a specific driving simulation platform to simulate VTT's unique hybrid autonomous/manual driving mode. The main contributions of this paper are as follows: First, a vehicle system dynamics (VSD) model of VTT was established using SIMPACK. Additionally, the control module for simulating the hybrid autonomous/manual driving mode of VTT was developed based on model predictive control and Logitech driving simulation hardware. Furthermore, a driving scene visualization interface was established using Unreal Engine and Blender to simulate the real driving environment. These components form a comprehensive simulation platform for the VTT. Simulation results demonstrate that the developed platform can effectively and accurately simulate the operational performance of the VTT under various driving modes, highlighting its significant engineering value.

An investigation into the current status of the smart operation and maintenance system for urban rail power substations has been conducted. The paper summarizes the challenges faced by the current comprehensive automation system scheduling and operation and maintenance methods of urban rail power substations, which are considered from aspects such as system architecture, hardware configuration, information conditions, dispatching mode, and operation and maintenance management. Requirements for the smart operation and maintenance system of urban rail power substations have been proposed. The overall framework of the smart operation and maintenance system for urban rail power substations has been designed; various independently constructed power supply subsystems have been integrated to form a unified dispatching and operation and maintenance platform, and the full life cycle data of equipment on both the power supply and distribution sides of the urban rail power supply system have been integrated. The smart operation and maintenance system for substations in the urban rail power supply field, which has been constructed, is applicable to the technical specifications of the urban rail cloud, addressing issues such as decentralized construction, inconsistent standards, and redundant investment in multiple subsystems and key equipment of the urban rail power supply system. It meets the current and future development needs of intelligent power supply systems.

The lowaltitude economy has become a new industrial direction pursued in global competition due to its prominent features. The research on lowaltitude economy in the field of urban rail transit is rapidly developing and growing. For the low and medium capacity rail transit systems represented by the straddle monorail system, based on the key technology research of low altitude technology, it is necessary to explore a low altitude unmanned aerial vehicle intelligent inspection system that is suitable for the construction and operation characteristics of straddle monorails, meets operational requirements, and effectively solves maintenance problems. This study proposes for the first time a video intelligent inspection system based on an unmanned aerial vehicle platform applied to straddle monorail transit, analyzes its application plan scheme and value in straddle monorail transit, and explores a practical and feasible low altitudeeconomic economy application scenario for the low and medium capacity rail transit systems mainly based on elevated laying structures. This approach is conducive to achieving the automation of straddletype monorail transit track beam and bridge inspection. This approach is effective in Reducing the workload of manual inspections and minimizing manual omissions has significant implications for the industry.

The existing decentralized rectification scheme for direct current (DC) lighting systems in metro stations faces several challenges, including low power supply reliability and efficiency, high cable costs, significant distribution losses, and difficulties in unified equipment maintenance and power quality management. To address these issues, this paper proposes a centralized rectification scheme for metro station DC lighting systems. The study begins with an analysis of the system architecture, current status, and limitations of the existing decentralized scheme, followed by a detailed presentation of the proposed centralized solution, including its system architecture, DC power supply configuration, key components, and required system modifications. A comprehensive comparison between the two schemes is conducted using actual engineering data, focusing on system losses, costs, harmonic content, and operational reliability. The results demonstrate that compared to the decentralized scheme, the centralized rectification scheme requires less feeder cable usage and achieves lower system costs. It also shows significant improvements in reducing cable losses, increasing system power efficiency, and decreasing harmonic content. Furthermore, the power modules in the centralized scheme operate under more favorable conditions, leading to enhanced system stability. Based on these advantages, the centralized rectification scheme proves to be a more suitable solution for DC lighting systems in metro stations.

This paper investigates potential applications of quantum communication technology in urban rail transit information systems, addressing current and emerging security challenges. Based on existing information system architectures in urban rail transit, we leverage the advantages of quantum key distribution networks for cryptographic applications and data security protection. The paper proposes integration strategies across multiple dimensions including secure computing environments, data storage, and data transmission. We specifically examine how quantum communication technology can enhance data security in computing environments, transmission processes, and storage systems. This research provides a framework for future applications of quantum communication technology in urban rail transit information systems.

To address the mismatch between urban rail transit construction and ridership efficiency in China, it is crucial to understand and master the influence laws of network ridership and improve efficiency. However, due to a lack of longitudinal data, research on the relationships between socioeconomic factors, network structure, and ridership remains insufficient. This study uses annual panel data from 2012 to 2020, calculates topological characteristics of the urban rail transit station network, and establishes a time fixedeffects model. The goal is to explore the topology of the urban rail transit network and its coupling relationship with urban layout effects on ridership changes, facilitating rational use of transit resources and improving core competitiveness. The results indicate that as the urban rail transit network develops, the complexity of the transportation network structure increases, and the number of interchange hubs rises, playing a crucial role in network connectivity. Changes in the topological variables of the urban rail transit network significantly enhance passenger flow; the densification of network distribution and regionalization of hubs help improve interchange connections and attract more passengers. The degree of coupling coordination significantly affects passenger flow changes; thus, the coupling relationship between population distribution and line layout should be considered according to local conditions in rail line network planning. Finally, this paper proposes relevant policy suggestions for rail transit network construction planning to provide a theoretical basis for urban rail transportation construction policy formulation.

To study the effectiveness and impact of rail transit development in developing countries and to improve urban development experiences based on the TransitOriented Development (TOD) model, this study takes the Addis Ababa Light Rail Transit (LRT) as a case study to analyze its effects on residents' commuting and the spatial distribution of jobs and residences after its completion. Based on official city maps, resident questionnaires, and interview data, a multiple linear regression model was employed to analyze the influence of different commuting methods on commuting time. The findings indicate that the light rail system has a limited effect on improving residents' commuting efficiency. Further GIS spatial analysis reveals that the overall distribution of residential and employment areas in the city is uneven, with suburban residential density being exceeding five times that of urban areas. The analysis results reflect that the failure to coordinate land use with the development of the light rail corridor is a primary reason for the low commuting efficiency. The conclusions advance the understanding of the adaptability and implementation strategies of the TransitOriented Development (TOD) model in countries with lowdensity sprawl and relatively underdeveloped economies.